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Sample records for georgia interactive network

  1. Network and computing infrastructure for scientific applications in Georgia

    Science.gov (United States)

    Kvatadze, R.; Modebadze, Z.

    2016-09-01

    Status of network and computing infrastructure and available services for research and education community of Georgia are presented. Research and Educational Networking Association - GRENA provides the following network services: Internet connectivity, network services, cyber security, technical support, etc. Computing resources used by the research teams are located at GRENA and at major state universities. GE-01-GRENA site is included in European Grid infrastructure. Paper also contains information about programs of Learning Center and research and development projects in which GRENA is participating.

  2. THE PROSPECTS OF DEVELOPMENT OF ELECTRIC POWER NETWORK IN GEORGIA

    International Nuclear Information System (INIS)

    Mshvidobadze, T.

    2007-01-01

    The possibility of application of one of the versions of development of the electric power network in Georgia is disscussed. The algorithm of grouping of the versions of power network development, which allows choosing the optimal network configuration under indefinite conditions, is offered. The experiments have demonstrated that the same optimal decision can be found by considerable reduction in the number of versions. (author)

  3. New strong motion network in Georgia: basis for specifying seismic hazard

    Science.gov (United States)

    Kvavadze, N.; Tsereteli, N. S.

    2017-12-01

    Risk created by hazardous natural events is closely related to sustainable development of the society. Global observations have confirmed tendency of growing losses resulting from natural disasters, one of the most dangerous and destructive if which are earthquakes. Georgia is located in seismically active region. So, it is imperative to evaluate probabilistic seismic hazard and seismic risk with proper accuracy. National network of Georgia includes 35 station all of which are seismometers. There are significant gaps in strong motion recordings, which essential for seismic hazard assessment. To gather more accelerometer recordings, we have built a strong motion network distributed on the territory of Georgia. The network includes 6 stations for now, with Basalt 4x datalogger and strong motion sensor Episensor ES-T. For each site, Vs30 and soil resonance frequencies have been measured. Since all but one station (Tabakhmelam near Tbilisi), are located far from power and internet lines special system was created for instrument operation. Solar power is used to supply the system with electricity and GSM/LTE modems for internet access. VPN tunnel was set up using Raspberry pi, for two-way communication with stations. Tabakhmela station is located on grounds of Ionosphere Observatory, TSU and is used as a hub for the network. This location also includes a broadband seismometer and VLF electromagnetic waves observation antenna, for possible earthquake precursor studies. On server, located in Tabakhmela, the continues data is collected from all the stations, for later use. The recordings later will be used in different seismological and engineering problems, namely selecting and creating GMPE model for Caucasus, for probabilistic seismic hazard and seismic risk evaluation. These stations are a start and in the future expansion of strong motion network is planned. Along with this, electromagnetic wave observations will continue and additional antennas will be implemented

  4. The results of the pilot project in Georgia to install a network of electromagnetic radiation before the earthquake

    Science.gov (United States)

    Machavariani, Kakhaber; Khazaradze, Giorgi; Turazashvili, Ioseb; Kachakhidze, Nino; Kachakhidze, Manana; Gogoberidze, Vitali

    2016-04-01

    The world's scientific literature recently published many very important and interesting works of VLF / LF electromagnetic emissions, which is observed in the process of earthquake preparation. This works reliable earthquake prediction in terms of trends. Because, Georgia is located in Trans Asian earthquake zone, VLF / LF electromagnetic emissions network are essential. In this regard, it was possible to take first steps. It is true that our university has Shota Rustaveli National Science Foundation № DI / 21 / 9-140 / 13 grant, which included the installation of a receiver in Georgia, but failed due to lack of funds to buy this device. However, European friends helped us (Prof. Dr. PF Biagi and Prof. Dr. Aydın BÜYÜKSARAÇ) and made possible the installation of a receiver. Turkish scientists expedition in Georgia was organized in August 2015. They brought with them VLF / LF electromagnetic emissions receiver and together with Georgian scientists install near Tbilisi. The station was named GEO-TUR. It should be noted that Georgia was involved in the work of the European network. It is possible to completely control the earthquake in Georgia in terms of electromagnetic radiation. This enables scientists to obtain the relevant information not only on the territory of our country, but also on seismically active European countries as well. In order to maintain and develop our country in this new direction, it is necessary to keep independent group of scientists who will learn electromagnetic radiation ahead of an earthquake in Georgia. At this stage, we need to remedy this shortcoming, it is necessary and appropriate specialists to Georgia to engage in a joint international research. The work is carried out in the frame of grant (DI/21/9-140/13 „Pilot project of before earthquake detected Very Low Frequency/Low Frequency electromagnetic emission network installation in Georgia") by financial support of Shota Rustaveli National Science Foundation.

  5. Georgia-Armenia Transboarder seismicity studies

    Science.gov (United States)

    Godoladze, T.; Tvaradze, N.; Javakishvili, Z.; Elashvili, M.; Durgaryan, R.; Arakelyan, A.; Gevorgyan, M.

    2012-12-01

    In the presented study we performed Comprehensive seismic analyses for the Armenian-Georgian transboarder active seismic fault starting on Armenian territory, cutting the state boarder and having possibly northern termination on Adjara-Triealeti frontal structure in Georgia. In the scope of International projects: ISTC A-1418 "Open network of scientific Centers for mitigation risk of natural hazards in the Southern Caucasus and Central Asia" and NATO SfP- 983284 Project "Caucasus Seismic Emergency Response" in Akhalkalaki (Georgia) seismic center, Regional Summer school trainings and intensive filed investigations were conducted. Main goal was multidisciplinary study of the Javakheti fault structure and better understanding seismicity of the area. Young scientists from Turkey, Armenia, Azerbaijan and Georgia were participated in the deployment of temporal seismic network in order to monitor seisimity on the Javakheti highland and particularly delineate fault scarf and identify active seismic structures. In the scope of international collaboration the common seismic database has been created in the southern Caucasus and collected data from the field works is available now online. Javakheti highland, which is located in the central part of the Caucasus, belongs to the structure of the lesser Caucasus and represents a history of neotectonic volcanism existed in the area. Jasvakheti highland is seismicalu active region devastating from several severe earthquakes(1088, 1283, 1899…). Hypocenters located during analogue network were highly scattered and did not describe real pattern of seismicity of the highland. We relocated hypocenters of the region and improved local velocity model. The hypocenters derived from recently deployed local seismic network in the Javakheti highland, clearly identified seismically active structures. Fault plane solutions of analogue data of the Soviet times have been carefully analyzed and examined. Moment tensor inversion were preformed

  6. Snapshots of biodiversity in Georgia agroecosystems

    Science.gov (United States)

    Georgia agricultural landscapes are composed of a diversity of commodities. Here we present biodiversity and biotic interaction data from multiple agricultural systems including: cotton, corn, peanut, blueberry and non-cropping wildflower areas over multiple years. Our goal is to better understand t...

  7. Return to normal streamflows and water levels: summary of hydrologic conditions in Georgia, 2013

    Science.gov (United States)

    Knaak, Andrew E.; Caslow, Kerry; Peck, Michael F.

    2015-01-01

    The U.S. Geological Survey (USGS) South Atlantic Water Science Center (SAWSC) Georgia office, in cooperation with local, State, and other Federal agencies, maintains a long-term hydrologic monitoring network of more than 340 real-time continuous-record streamflow-gaging stations (streamgages), including 10 real-time lake-level monitoring stations, 67 real-time surface-water-quality monitors, and several water-quality sampling programs. Additionally, the SAWSC Georgia office operates more than 180 groundwater monitoring wells, 39 of which are real-time. The wide-ranging coverage of streamflow, reservoir, and groundwater monitoring sites allows for a comprehensive view of hydrologic conditions across the State. One of the many benefits of this monitoring network is that the analyses of the data provide a spatially distributed overview of the hydrologic conditions of creeks, rivers, reservoirs, and aquifers in Georgia.

  8. Delineating groundwater/surface water interaction in a karst watershed: Lower Flint River Basin, southwestern Georgia, USA

    Directory of Open Access Journals (Sweden)

    Kathleen Rugel

    2016-03-01

    Full Text Available Study region: Karst watershed in Lower Flint River Basin (LFRB, southwestern Georgia, USA. Study focus: Baseflow discharges in the LFRB have declined for three decades as regional irrigation has increased; yet, the location and nature of connectivity between groundwater and surface water in this karstic region are poorly understood. Because growing water demands will likely be met by further development of regional aquifers, an important management concern is the nature of interactions between groundwater and surface water components under natural and anthropogenic perturbations. We conducted coarse and fine-scale stream sampling on a major tributary of the Lower Flint River (Ichawaynochaway Creek in southwestern Georgia, USA, to identify locations and patterns of enhanced hydrologic connectivity between this stream and the Upper Floridan Aquifer. New hydrological insights for the region: Prior water resource studies in the LFRB were based on regional modeling that neglected local heterogeneities in groundwater/surface water connectivity. Our results demonstrated groundwater inputs were concentrated around five of fifty sampled reaches, evidenced by increases in multiple groundwater indicators at these sites. These five reaches contributed up to 42% of the groundwater detected along the entire 50-km sampling section, with ∼24% entering through one groundwater-dominated tributary, Chickasawhatchee Creek. Intermittent flows occurred in two of these upstream reaches during extreme drought and heavy groundwater pumping, suggesting reach-scale behaviors should be considered in resource management and policy. Keywords: Karst hydrogeology, Hydrologic connectivity, Groundwater/surface water interaction, Upper Floridan Aquifer, Groundwater Irrigation

  9. Statistical Mechanics of Temporal and Interacting Networks

    Science.gov (United States)

    Zhao, Kun

    In the last ten years important breakthroughs in the understanding of the topology of complexity have been made in the framework of network science. Indeed it has been found that many networks belong to the universality classes called small-world networks or scale-free networks. Moreover it was found that the complex architecture of real world networks strongly affects the critical phenomena defined on these structures. Nevertheless the main focus of the research has been the characterization of single and static networks. Recently, temporal networks and interacting networks have attracted large interest. Indeed many networks are interacting or formed by a multilayer structure. Example of these networks are found in social networks where an individual might be at the same time part of different social networks, in economic and financial networks, in physiology or in infrastructure systems. Moreover, many networks are temporal, i.e. the links appear and disappear on the fast time scale. Examples of these networks are social networks of contacts such as face-to-face interactions or mobile-phone communication, the time-dependent correlations in the brain activity and etc. Understanding the evolution of temporal and multilayer networks and characterizing critical phenomena in these systems is crucial if we want to describe, predict and control the dynamics of complex system. In this thesis, we investigate several statistical mechanics models of temporal and interacting networks, to shed light on the dynamics of this new generation of complex networks. First, we investigate a model of temporal social networks aimed at characterizing human social interactions such as face-to-face interactions and phone-call communication. Indeed thanks to the availability of data on these interactions, we are now in the position to compare the proposed model to the real data finding good agreement. Second, we investigate the entropy of temporal networks and growing networks , to provide

  10. Georgia's Workforce Development Pipeline: One District's Journey

    Science.gov (United States)

    Williams, Melissa H.; Hufstetler, Tammy L.

    2011-01-01

    Launched in 2006, the Georgia Work Ready initiative seeks to improve the job training and marketability of Georgia's workforce and drive the state's economic growth. Georgia Work Ready is a partnership between the state and the Georgia Chamber of Commerce. Comprised of three components, Georgia's initiative focuses on job profiling, skills…

  11. 76 FR 25330 - Georgia Power Company; Project No. 485-063-Georgia and Alabama, Bartletts Ferry Hydroelectric...

    Science.gov (United States)

    2011-05-04

    ... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission Georgia Power Company; Project No. 485-063--Georgia and Alabama, Bartletts Ferry Hydroelectric Project; Notice of Proposed Restricted Service... Ferry Hydroelectric Project. The Programmatic Agreement, when executed by the Commission, the Georgia...

  12. Network Physiology: How Organ Systems Dynamically Interact

    Science.gov (United States)

    Bartsch, Ronny P.; Liu, Kang K. L.; Bashan, Amir; Ivanov, Plamen Ch.

    2015-01-01

    We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems. PMID:26555073

  13. Network Physiology: How Organ Systems Dynamically Interact.

    Science.gov (United States)

    Bartsch, Ronny P; Liu, Kang K L; Bashan, Amir; Ivanov, Plamen Ch

    2015-01-01

    We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems.

  14. Evidence for the additions of clustered interacting nodes during the evolution of protein interaction networks from network motifs

    Directory of Open Access Journals (Sweden)

    Guo Hao

    2011-05-01

    Full Text Available Abstract Background High-throughput screens have revealed large-scale protein interaction networks defining most cellular functions. How the proteins were added to the protein interaction network during its growth is a basic and important issue. Network motifs represent the simplest building blocks of cellular machines and are of biological significance. Results Here we study the evolution of protein interaction networks from the perspective of network motifs. We find that in current protein interaction networks, proteins of the same age class tend to form motifs and such co-origins of motif constituents are affected by their topologies and biological functions. Further, we find that the proteins within motifs whose constituents are of the same age class tend to be densely interconnected, co-evolve and share the same biological functions, and these motifs tend to be within protein complexes. Conclusions Our findings provide novel evidence for the hypothesis of the additions of clustered interacting nodes and point out network motifs, especially the motifs with the dense topology and specific function may play important roles during this process. Our results suggest functional constraints may be the underlying driving force for such additions of clustered interacting nodes.

  15. Hazard interactions and interaction networks (cascades) within multi-hazard methodologies

    Science.gov (United States)

    Gill, Joel C.; Malamud, Bruce D.

    2016-08-01

    This paper combines research and commentary to reinforce the importance of integrating hazard interactions and interaction networks (cascades) into multi-hazard methodologies. We present a synthesis of the differences between multi-layer single-hazard approaches and multi-hazard approaches that integrate such interactions. This synthesis suggests that ignoring interactions between important environmental and anthropogenic processes could distort management priorities, increase vulnerability to other spatially relevant hazards or underestimate disaster risk. In this paper we proceed to present an enhanced multi-hazard framework through the following steps: (i) description and definition of three groups (natural hazards, anthropogenic processes and technological hazards/disasters) as relevant components of a multi-hazard environment, (ii) outlining of three types of interaction relationship (triggering, increased probability, and catalysis/impedance), and (iii) assessment of the importance of networks of interactions (cascades) through case study examples (based on the literature, field observations and semi-structured interviews). We further propose two visualisation frameworks to represent these networks of interactions: hazard interaction matrices and hazard/process flow diagrams. Our approach reinforces the importance of integrating interactions between different aspects of the Earth system, together with human activity, into enhanced multi-hazard methodologies. Multi-hazard approaches support the holistic assessment of hazard potential and consequently disaster risk. We conclude by describing three ways by which understanding networks of interactions contributes to the theoretical and practical understanding of hazards, disaster risk reduction and Earth system management. Understanding interactions and interaction networks helps us to better (i) model the observed reality of disaster events, (ii) constrain potential changes in physical and social vulnerability

  16. Georgia Public Health Laboratory, Decatur, Georgia

    Energy Technology Data Exchange (ETDEWEB)

    2002-12-01

    This case study was prepared as one in a series for the Laboratories for the 21st Century program, a joint endeavor of the U.S. Environmental Protection Agency and the U.S. Department of Energy's Federal Energy Management Program. The goal of this program is to foster greater energy efficiency in new and retrofit laboratory buildings in both the public and the private sectors. The energy-efficient elements of the laboratory featured in this case study-the Georgia Public Health Laboratory, Decatur, Georgia-include sustainable design features, light-filled interior spaces for daylighting, closely grouped loads (such as freezers), the use of recirculated air in administrative areas, direct digital controls for heating and cooling equipment, sunscreens, and low-emissivity window glazing. These elements, combined with an attractive design and well-lighted work spaces, add up to a building that ranks high in comfort and low in energy use.

  17. Discerning molecular interactions: A comprehensive review on biomolecular interaction databases and network analysis tools.

    Science.gov (United States)

    Miryala, Sravan Kumar; Anbarasu, Anand; Ramaiah, Sudha

    2018-02-05

    Computational analysis of biomolecular interaction networks is now gaining a lot of importance to understand the functions of novel genes/proteins. Gene interaction (GI) network analysis and protein-protein interaction (PPI) network analysis play a major role in predicting the functionality of interacting genes or proteins and gives an insight into the functional relationships and evolutionary conservation of interactions among the genes. An interaction network is a graphical representation of gene/protein interactome, where each gene/protein is a node, and interaction between gene/protein is an edge. In this review, we discuss the popular open source databases that serve as data repositories to search and collect protein/gene interaction data, and also tools available for the generation of interaction network, visualization and network analysis. Also, various network analysis approaches like topological approach and clustering approach to study the network properties and functional enrichment server which illustrates the functions and pathway of the genes and proteins has been discussed. Hence the distinctive attribute mentioned in this review is not only to provide an overview of tools and web servers for gene and protein-protein interaction (PPI) network analysis but also to extract useful and meaningful information from the interaction networks. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Wind Power in Georgia

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2012-11-01

    Georgia has good wind power potential. Preliminary analyses show that the technical wind power potential in Georgia is good. Meteorological data shows that Georgia has four main areas in Georgia with annual average wind speeds of over 6 m/s and two main areas with 5-6 m/s at 80m. The most promising areas are the high mountain zone of the Great Caucasus, The Kura river valley, The South-Georgian highland and the Southern part of the Georgian Black Sea coast. Czech company Wind Energy Invest has recently signed a Memorandum of Understanding with Georgian authorities for development of the first wind farm in Georgia, a 50MW wind park in Paravani, Southern Georgia, to be completed in 2014. Annual generation is estimated to 170.00 GWh and the investment estimated to 101 million US$. Wind power is suited to balance hydropower in the Georgian electricity sector Electricity generation in Georgia is dominated by hydro power, constituting 88% of total generation in 2009. Limited storage capacity and significant spring and summer peaks in river flows result in an uneven annual generation profile and winter time shortages that are covered by three gas power plants. Wind power is a carbon-free energy source well suited to balance hydropower, as it is available (often strongest) in the winter and can be exported when there is a surplus. Another advantage with wind power is the lead time for the projects; the time from site selection to operation for a wind power park (approximately 2.5 years) is much shorter than for hydro power (often 6-8 years). There is no support system or scheme for renewable sources in Georgia, so wind power has to compete directly with other energy sources and is in most cases more expensive to build than hydro power. In a country and region with rapidly increasing energy demands, the factors described above nevertheless indicate that there is a commercial niche and a role to play for Georgian wind power. Skra: An example of a wind power development

  19. Game theory in communication networks cooperative resolution of interactive networking scenarios

    CERN Document Server

    Antoniou, Josephina

    2012-01-01

    A mathematical tool for scientists and researchers who work with computer and communication networks, Game Theory in Communication Networks: Cooperative Resolution of Interactive Networking Scenarios addresses the question of how to promote cooperative behavior in interactive situations between heterogeneous entities in communication networking scenarios. It explores network design and management from a theoretical perspective, using game theory and graph theory to analyze strategic situations and demonstrate profitable behaviors of the cooperative entities. The book promotes the use of Game T

  20. Unraveling spurious properties of interaction networks with tailored random networks.

    Directory of Open Access Journals (Sweden)

    Stephan Bialonski

    Full Text Available We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures--known for their complex spatial and temporal dynamics--we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.

  1. Women Politicians and Parliamentary Elections in Ukraine and Georgia in 2012

    Directory of Open Access Journals (Sweden)

    Tetiana Kostiuchenko

    2015-09-01

    Full Text Available Abstract: Post-communist countries undergoing social transformations in the last twenty years needed to implement political and economic reforms. Changes also had to support the principles of equality in the access to power, specifically gender quotas in executive and legislative branches of government and within political parties. The events in Ukraine and Georgia in 2004-2005 known as the “colour revolutions” gave impulse to the promotion of equality and implementation of reforms. However, the number of women participating in national politics in both countries remains low. This paper proposes an analysis of gender equality principles during the parliamentary election campaigns in Ukraine and Georgia in 2012 from the perspective of women’s participation in politics and their self-representation as politicians. This empirical study covers public attitudes towards women in politics and examines networks of female parliamentarians. The findings raise hopes for better representation of women in politics as female politicians promote them from the top down, and mass public perception of gender equality principles set the ground for bottom-up activism. Keywords: Gender Equality, Women Politicians, Public Attitudes, Social Network Analysis (SNA

  2. Modeling the live-pig trade network in Georgia: Implications for disease prevention and control.

    Directory of Open Access Journals (Sweden)

    Esther Andrea Kukielka

    Full Text Available Live pig trade patterns, drivers and characteristics, particularly in backyard predominant systems, remain largely unexplored despite their important contribution to the spread of infectious diseases in the swine industry. A better understanding of the pig trade dynamics can inform the implementation of risk-based and more cost-effective prevention and control programs for swine diseases. In this study, a semi-structured questionnaire elaborated by FAO and implemented to 487 farmers was used to collect data regarding basic characteristics about pig demographics and live-pig trade among villages in the country of Georgia, where very scarce information is available. Social network analysis and exponential random graph models were used to better understand the structure, contact patterns and main drivers for pig trade in the country. Results indicate relatively infrequent (a total of 599 shipments in one year and geographically localized (median Euclidean distance between shipments = 6.08 km; IQR = 0-13.88 km pig movements in the studied regions. The main factors contributing to live-pig trade movements among villages were being from the same region (i.e., local trade, usage of a middleman or a live animal market to trade live pigs by at least one farmer in the village, and having a large number of pig farmers in the village. The identified villages' characteristics and structural network properties could be used to inform the design of more cost-effective surveillance systems in a country which pig industry was recently devastated by African swine fever epidemics and where backyard production systems are predominant.

  3. Defaunation leads to interaction deficits, not interaction compensation, in an island seed dispersal network.

    Science.gov (United States)

    Fricke, Evan C; Tewksbury, Joshua J; Rogers, Haldre S

    2018-01-01

    Following defaunation, the loss of interactions with mutualists such as pollinators or seed dispersers may be compensated through increased interactions with remaining mutualists, ameliorating the negative cascading impacts on biodiversity. Alternatively, remaining mutualists may respond to altered competition by reducing the breadth or intensity of their interactions, exacerbating negative impacts on biodiversity. Despite the importance of these responses for our understanding of the dynamics of mutualistic networks and their response to global change, the mechanism and magnitude of interaction compensation within real mutualistic networks remains largely unknown. We examined differences in mutualistic interactions between frugivores and fruiting plants in two island ecosystems possessing an intact or disrupted seed dispersal network. We determined how changes in the abundance and behavior of remaining seed dispersers either increased mutualistic interactions (contributing to "interaction compensation") or decreased interactions (causing an "interaction deficit") in the disrupted network. We found a "rich-get-richer" response in the disrupted network, where remaining frugivores favored the plant species with highest interaction frequency, a dynamic that worsened the interaction deficit among plant species with low interaction frequency. Only one of five plant species experienced compensation and the other four had significant interaction deficits, with interaction frequencies 56-95% lower in the disrupted network. These results do not provide support for the strong compensating mechanisms assumed in theoretical network models, suggesting that existing network models underestimate the prevalence of cascading mutualism disruption after defaunation. This work supports a mutualist biodiversity-ecosystem functioning relationship, highlighting the importance of mutualist diversity for sustaining diverse and resilient ecosystems. © 2017 John Wiley & Sons Ltd.

  4. Social Interaction in Learning Networks

    NARCIS (Netherlands)

    Sloep, Peter

    2009-01-01

    The original publication is available from www.springerlink.com. Sloep, P. (2009). Social Interaction in Learning Networks. In R. Koper (Ed.), Learning Network Services for Professional Development (pp 13-15). Berlin, Germany: Springer Verlag.

  5. Statistical physics of interacting neural networks

    Science.gov (United States)

    Kinzel, Wolfgang; Metzler, Richard; Kanter, Ido

    2001-12-01

    Recent results on the statistical physics of time series generation and prediction are presented. A neural network is trained on quasi-periodic and chaotic sequences and overlaps to the sequence generator as well as the prediction errors are calculated numerically. For each network there exists a sequence for which it completely fails to make predictions. Two interacting networks show a transition to perfect synchronization. A pool of interacting networks shows good coordination in the minority game-a model of competition in a closed market. Finally, as a demonstration, a perceptron predicts bit sequences produced by human beings.

  6. Georgia’s Brightest Future Includes Russia

    Science.gov (United States)

    2012-03-01

    should not automatically signal that Georgia is doomed to the stagnation, interference and corruption that normally permeate Russian satellite...associated with Russian tourism . Though Russian tourism is growing in Georgia and represented 8% of their total visitors in 2010, 58 they could...to Russian markets once again. 58 Georgia National Tourism Agency official statistics, http://www.gnta.ge/?61/statistics/&lan=en, Chart entitled

  7. Specific non-monotonous interactions increase persistence of ecological networks.

    Science.gov (United States)

    Yan, Chuan; Zhang, Zhibin

    2014-03-22

    The relationship between stability and biodiversity has long been debated in ecology due to opposing empirical observations and theoretical predictions. Species interaction strength is often assumed to be monotonically related to population density, but the effects on stability of ecological networks of non-monotonous interactions that change signs have not been investigated previously. We demonstrate that for four kinds of non-monotonous interactions, shifting signs to negative or neutral interactions at high population density increases persistence (a measure of stability) of ecological networks, while for the other two kinds of non-monotonous interactions shifting signs to positive interactions at high population density decreases persistence of networks. Our results reveal a novel mechanism of network stabilization caused by specific non-monotonous interaction types through either increasing stable equilibrium points or reducing unstable equilibrium points (or both). These specific non-monotonous interactions may be important in maintaining stable and complex ecological networks, as well as other networks such as genes, neurons, the internet and human societies.

  8. Evolution of a protein domain interaction network

    International Nuclear Information System (INIS)

    Li-Feng, Gao; Jian-Jun, Shi; Shan, Guan

    2010-01-01

    In this paper, we attempt to understand complex network evolution from the underlying evolutionary relationship between biological organisms. Firstly, we construct a Pfam domain interaction network for each of the 470 completely sequenced organisms, and therefore each organism is correlated with a specific Pfam domain interaction network; secondly, we infer the evolutionary relationship of these organisms with the nearest neighbour joining method; thirdly, we use the evolutionary relationship between organisms constructed in the second step as the evolutionary course of the Pfam domain interaction network constructed in the first step. This analysis of the evolutionary course shows: (i) there is a conserved sub-network structure in network evolution; in this sub-network, nodes with lower degree prefer to maintain their connectivity invariant, and hubs tend to maintain their role as a hub is attached preferentially to new added nodes; (ii) few nodes are conserved as hubs; most of the other nodes are conserved as one with very low degree; (iii) in the course of network evolution, new nodes are added to the network either individually in most cases or as clusters with relative high clustering coefficients in a very few cases. (general)

  9. Topology of molecular interaction networks

    NARCIS (Netherlands)

    Winterbach, W.; Van Mieghem, P.; Reinders, M.; Wang, H.; De Ridder, D.

    2013-01-01

    Molecular interactions are often represented as network models which have become the common language of many areas of biology. Graphs serve as convenient mathematical representations of network models and have themselves become objects of study. Their topology has been intensively researched over

  10. Demonstration Exercise of a Validated Sample Collection Method for Powders Suspected of Being Biological Agents in Georgia 2006

    International Nuclear Information System (INIS)

    Marsh, B.

    2007-01-01

    August 7, 2006 the state of Georgia conducted a collaborative sampling exercise between the Georgia National Guard 4th Civil Support Team Weapons of Mass Destruction (CST-WMD) and the Georgia Department of Human Resources Division of Public Health demonstrating a recently validated bulk powder sampling method. The exercise was hosted at the Federal Law Enforcement Training Center (FLETC) at Glynn County, Georgia and involved the participation of the Georgia Emergency Management Agency (GEMA), Georgia National Guard, Georgia Public Health Laboratories, the Federal Bureau of Investigation Atlanta Office, Georgia Coastal Health District, and the Glynn County Fire Department. The purpose of the exercise was to demonstrate a recently validated national sampling standard developed by the American Standards and Test Measures (ASTM) International; ASTM E2458 S tandard Practice for Bulk Sample Collection and Swab Sample Collection of Visible Powders Suspected of Being Biological Agents from Nonporous Surfaces . The intent of the exercise was not to endorse the sampling method, but to develop a model for exercising new sampling methods in the context of existing standard operating procedures (SOPs) while strengthening operational relationships between response teams and analytical laboratories. The exercise required a sampling team to respond real-time to an incident cross state involving a clandestine bio-terrorism production lab found within a recreational vehicle (RV). Sample targets consisted of non-viable gamma irradiated B. anthracis Sterne spores prepared by Dugway Proving Ground. Various spore concentration levels were collected by the ASTM method, followed by on- and off-scene analysis utilizing the Center for Disease Control (CDC) Laboratory Response Network (LRN) and National Guard Bureau (NGB) CST mobile Analytical Laboratory Suite (ALS) protocols. Analytical results were compared and detailed surveys of participant evaluation comments were examined. I will

  11. Influence of degree correlations on network structure and stability in protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Zimmer Ralf

    2007-08-01

    Full Text Available Abstract Background The existence of negative correlations between degrees of interacting proteins is being discussed since such negative degree correlations were found for the large-scale yeast protein-protein interaction (PPI network of Ito et al. More recent studies observed no such negative correlations for high-confidence interaction sets. In this article, we analyzed a range of experimentally derived interaction networks to understand the role and prevalence of degree correlations in PPI networks. We investigated how degree correlations influence the structure of networks and their tolerance against perturbations such as the targeted deletion of hubs. Results For each PPI network, we simulated uncorrelated, positively and negatively correlated reference networks. Here, a simple model was developed which can create different types of degree correlations in a network without changing the degree distribution. Differences in static properties associated with degree correlations were compared by analyzing the network characteristics of the original PPI and reference networks. Dynamics were compared by simulating the effect of a selective deletion of hubs in all networks. Conclusion Considerable differences between the network types were found for the number of components in the original networks. Negatively correlated networks are fragmented into significantly less components than observed for positively correlated networks. On the other hand, the selective deletion of hubs showed an increased structural tolerance to these deletions for the positively correlated networks. This results in a lower rate of interaction loss in these networks compared to the negatively correlated networks and a decreased disintegration rate. Interestingly, real PPI networks are most similar to the randomly correlated references with respect to all properties analyzed. Thus, although structural properties of networks can be modified considerably by degree

  12. Interaction Networks: Generating High Level Hints Based on Network Community Clustering

    Science.gov (United States)

    Eagle, Michael; Johnson, Matthew; Barnes, Tiffany

    2012-01-01

    We introduce a novel data structure, the Interaction Network, for representing interaction-data from open problem solving environment tutors. We show how using network community detecting techniques are used to identify sub-goals in problems in a logic tutor. We then use those community structures to generate high level hints between sub-goals.…

  13. Structure of the human chromosome interaction network.

    Directory of Open Access Journals (Sweden)

    Sergio Sarnataro

    Full Text Available New Hi-C technologies have revealed that chromosomes have a complex network of spatial contacts in the cell nucleus of higher organisms, whose organisation is only partially understood. Here, we investigate the structure of such a network in human GM12878 cells, to derive a large scale picture of nuclear architecture. We find that the intensity of intra-chromosomal interactions is power-law distributed. Inter-chromosomal interactions are two orders of magnitude weaker and exponentially distributed, yet they are not randomly arranged along the genomic sequence. Intra-chromosomal contacts broadly occur between epigenomically homologous regions, whereas inter-chromosomal contacts are especially associated with regions rich in highly expressed genes. Overall, genomic contacts in the nucleus appear to be structured as a network of networks where a set of strongly individual chromosomal units, as envisaged in the 'chromosomal territory' scenario derived from microscopy, interact with each other via on average weaker, yet far from random and functionally important interactions.

  14. Synchronization in networks with multiple interaction layers

    Science.gov (United States)

    del Genio, Charo I.; Gómez-Gardeñes, Jesús; Bonamassa, Ivan; Boccaletti, Stefano

    2016-01-01

    The structure of many real-world systems is best captured by networks consisting of several interaction layers. Understanding how a multilayered structure of connections affects the synchronization properties of dynamical systems evolving on top of it is a highly relevant endeavor in mathematics and physics and has potential applications in several socially relevant topics, such as power grid engineering and neural dynamics. We propose a general framework to assess the stability of the synchronized state in networks with multiple interaction layers, deriving a necessary condition that generalizes the master stability function approach. We validate our method by applying it to a network of Rössler oscillators with a double layer of interactions and show that highly rich phenomenology emerges from this. This includes cases where the stability of synchronization can be induced even if both layers would have individually induced unstable synchrony, an effect genuinely arising from the true multilayer structure of the interactions among the units in the network. PMID:28138540

  15. Mortality in infants discharged from neonatal intensive care units in Georgia.

    Science.gov (United States)

    Allen, D M; Buehler, J W; Samuels, B N; Brann, A W

    Although neonatal intensive care units (NICUs) have contributed to advances in neonatal survival, little is known about the epidemiology of deaths that occur after NICU discharge. To determine mortality rates following NICU discharge, we used linked birth, death, and NICU records for infants born to Georgia residents from 1980 through 1982 and who were admitted to NICUs participating in the state's perinatal care network. Infants who died after discharge (n = 120) had a median duration of NICU hospitalization of 20 days (range, 1 to 148 days) and a median birth weight of 1983 g (range, 793 to 5159 g). The postdischarge mortality rate was 22.7 per 1000 NICU discharges. This rate is more than five times the overall postneonatal mortality rate for Georgia from 1980 to 1982. The most common causes of death were congenital heart disease (23%), sudden infant death syndrome (21%), and infection (13%). Demographic characteristics commonly associated with infant mortality were not strongly associated with the mortality following NICU discharge.

  16. Network Compression as a Quality Measure for Protein Interaction Networks

    Science.gov (United States)

    Royer, Loic; Reimann, Matthias; Stewart, A. Francis; Schroeder, Michael

    2012-01-01

    With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients. PMID:22719828

  17. Georgia - Energy Rehabilitation

    Data.gov (United States)

    Millennium Challenge Corporation — Gustavson Associates was retained by Millennium Challenge Georgia (MCG) to prepare a model to calculate the economic rate of return (ERR) for rehabilitation work...

  18. Do networks of social interactions reflect patterns of kinship?

    Institute of Scientific and Technical Information of China (English)

    Joah R. MADDEN; Johanna F. NIEL SEN; Tim H. CLUTTON-BROCK

    2012-01-01

    The underlying kin structure of groups of animals may be glimpsed from patterns of spatial position or temporal association between individuals,and is presumed to facilitate inclusive fitness benefits.Such structure may be evident at a finer,behavioural,scale with individuals preferentially interacting with kin.We tested whether kin structure within groups of meerkats Suricata suricatta matched three forms of social interaction networks:grooming,dominance or foraging competitions.Networks of dominance interactions were positively related to networks of kinship,with close relatives engaging in dominance interactions with each other.This relationship persisted even after excluding the breeding dominant pair and when we restricted the kinship network to only include links between first order kin,which are most likely to be able to discern kin through simple rules of thumb.Conversely,we found no relationship between kinship networks and either grooming networks or networks of foraging competitions.This is surprising because a positive association between kin in a grooming network,or a negative association between kin in a network of foraging competitions offers opportunities for inclusive fitness benefits.Indeed,the positive association between kin in a network of dominance interactions that we did detect does not offer clear inclusive fitness benefits to group members.We conclude that kin structure in behavioural interactions in meerkats may be driven by factors other than indirect fitness benefits,and that networks of cooperative behaviours such as grooming may be driven by direct benefits accruing to individuals perhaps through mutualism or manipulation [Current Zoology 58 (2):319-328,2012].

  19. Do networks of social interactions reflect patterns of kinship?

    Directory of Open Access Journals (Sweden)

    Joah R. MADDEN, Johanna F. NIELSEN, Tim H. CLUTTON-BROCK

    2012-04-01

    Full Text Available The underlying kin structure of groups of animals may be glimpsed from patterns of spatial position or temporal association between individuals, and is presumed to facilitate inclusive fitness benefits. Such structure may be evident at a finer, behavioural, scale with individuals preferentially interacting with kin. We tested whether kin structure within groups of meerkats Suricata suricatta matched three forms of social interaction networks: grooming, dominance or foraging competitions. Networks of dominance interactions were positively related to networks of kinship, with close relatives engaging in dominance interactions with each other. This relationship persisted even after excluding the breeding dominant pair and when we restricted the kinship network to only include links between first order kin, which are most likely to be able to discern kin through simple rules of thumb. Conversely, we found no relationship between kinship networks and either grooming networks or networks of foraging competitions. This is surprising because a positive association between kin in a grooming network, or a negative association between kin in a network of foraging competitions offers opportunities for inclusive fitness benefits. Indeed, the positive association between kin in a network of dominance interactions that we did detect does not offer clear inclusive fitness benefits to group members. We conclude that kin structure in behavioural interactions in meerkats may be driven by factors other than indirect fitness benefits, and that networks of cooperative behaviours such as grooming may be driven by direct benefits accruing to individuals perhaps through mutualism or manipulation [Current Zoology 58 (2: 319-328, 2012].

  20. Vertical Land Movements and Sea Level Changes around South Georgia Island

    OpenAIRE

    Teferle, Felix Norman; Hunegnaw, Addisu; Abraha, Kibrom Ebuy; Woodworth, Phil; Williams, Simon; Hibbert, Angela; Smalley, Robert; Dalziel, Ian; Lawver, Larry

    2018-01-01

    South Georgia Island in the Southern Atlantic Ocean is a key location for the seismic, geomagnetic and oceanic global monitoring networks. In its sub-Antarctic location, the island is largely covered by mountain glaciers which have been reported to be retreating due to climatic change. Furthermore, during past glaciation periods the island and its shelf area have been ice covered as was revealed by scarring of the sub-oceanic topography. Together with ongoing tectonics along the North Scotia ...

  1. Functional Interaction Network Construction and Analysis for Disease Discovery.

    Science.gov (United States)

    Wu, Guanming; Haw, Robin

    2017-01-01

    Network-based approaches project seemingly unrelated genes or proteins onto a large-scale network context, therefore providing a holistic visualization and analysis platform for genomic data generated from high-throughput experiments, reducing the dimensionality of data via using network modules and increasing the statistic analysis power. Based on the Reactome database, the most popular and comprehensive open-source biological pathway knowledgebase, we have developed a highly reliable protein functional interaction network covering around 60 % of total human genes and an app called ReactomeFIViz for Cytoscape, the most popular biological network visualization and analysis platform. In this chapter, we describe the detailed procedures on how this functional interaction network is constructed by integrating multiple external data sources, extracting functional interactions from human curated pathway databases, building a machine learning classifier called a Naïve Bayesian Classifier, predicting interactions based on the trained Naïve Bayesian Classifier, and finally constructing the functional interaction database. We also provide an example on how to use ReactomeFIViz for performing network-based data analysis for a list of genes.

  2. Global patterns of interaction specialization in bird-flower networks

    DEFF Research Database (Denmark)

    Zanata, Thais B.; Dalsgaard, Bo; Passos, Fernando C.

    2017-01-01

    , such as plant species richness, asymmetry, latitude, insularity, topography, sampling methods and intensity. Results: Hummingbird–flower networks were more specialized than honeyeater–flower networks. Specifically, hummingbird–flower networks had a lower proportion of realized interactions (lower C), decreased...... in the interaction patterns with their floral resources. Location: Americas, Africa, Asia and Oceania/Australia. Methods: We compiled interaction networks between birds and floral resources for 79 hummingbird, nine sunbird and 33 honeyeater communities. Interaction specialization was quantified through connectance...... (C), complementary specialization (H2′), binary (QB) and weighted modularity (Q), with both observed and null-model corrected values. We compared interaction specialization among the three types of bird–flower communities, both independently and while controlling for potential confounding variables...

  3. Interactive Network Exploration with Orange

    Directory of Open Access Journals (Sweden)

    Miha Štajdohar

    2013-04-01

    Full Text Available Network analysis is one of the most widely used techniques in many areas of modern science. Most existing tools for that purpose are limited to drawing networks and computing their basic general characteristics. The user is not able to interactively and graphically manipulate the networks, select and explore subgraphs using other statistical and data mining techniques, add and plot various other data within the graph, and so on. In this paper we present a tool that addresses these challenges, an add-on for exploration of networks within the general component-based environment Orange.

  4. A conserved mammalian protein interaction network.

    Directory of Open Access Journals (Sweden)

    Åsa Pérez-Bercoff

    Full Text Available Physical interactions between proteins mediate a variety of biological functions, including signal transduction, physical structuring of the cell and regulation. While extensive catalogs of such interactions are known from model organisms, their evolutionary histories are difficult to study given the lack of interaction data from phylogenetic outgroups. Using phylogenomic approaches, we infer a upper bound on the time of origin for a large set of human protein-protein interactions, showing that most such interactions appear relatively ancient, dating no later than the radiation of placental mammals. By analyzing paired alignments of orthologous and putatively interacting protein-coding genes from eight mammals, we find evidence for weak but significant co-evolution, as measured by relative selective constraint, between pairs of genes with interacting proteins. However, we find no strong evidence for shared instances of directional selection within an interacting pair. Finally, we use a network approach to show that the distribution of selective constraint across the protein interaction network is non-random, with a clear tendency for interacting proteins to share similar selective constraints. Collectively, the results suggest that, on the whole, protein interactions in mammals are under selective constraint, presumably due to their functional roles.

  5. Drug-domain interaction networks in myocardial infarction.

    Science.gov (United States)

    Wang, Haiying; Zheng, Huiru; Azuaje, Francisco; Zhao, Xing-Ming

    2013-09-01

    It has been well recognized that the pace of the development of new drugs and therapeutic interventions lags far behind biological knowledge discovery. Network-based approaches have emerged as a promising alternative to accelerate the discovery of new safe and effective drugs. Based on the integration of several biological resources including two recently published datasets i.e., Drug-target interactions in myocardial infarction (My-DTome) and drug-domain interaction network, this paper reports the association between drugs and protein domains in the context of myocardial infarction (MI). A MI drug-domain interaction network, My-DDome, was firstly constructed, followed by topological analysis and functional characterization of the network. The results show that My-DDome has a very clear modular structure, where drugs interacting with the same domain(s) within each module tend to have similar therapeutic effects. Moreover it has been found that drugs acting on blood and blood forming organs (ATC code B) and sensory organs (ATC code S) are significantly enriched in My-DDome (p drugs, their known targets, and seemingly unrelated proteins can be revealed.

  6. Specificity and evolvability in eukaryotic protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Pedro Beltrao

    2007-02-01

    Full Text Available Progress in uncovering the protein interaction networks of several species has led to questions of what underlying principles might govern their organization. Few studies have tried to determine the impact of protein interaction network evolution on the observed physiological differences between species. Using comparative genomics and structural information, we show here that eukaryotic species have rewired their interactomes at a fast rate of approximately 10(-5 interactions changed per protein pair, per million years of divergence. For Homo sapiens this corresponds to 10(3 interactions changed per million years. Additionally we find that the specificity of binding strongly determines the interaction turnover and that different biological processes show significantly different link dynamics. In particular, human proteins involved in immune response, transport, and establishment of localization show signs of positive selection for change of interactions. Our analysis suggests that a small degree of molecular divergence can give rise to important changes at the network level. We propose that the power law distribution observed in protein interaction networks could be partly explained by the cell's requirement for different degrees of protein binding specificity.

  7. Enhancing the Functional Content of Eukaryotic Protein Interaction Networks

    Science.gov (United States)

    Pandey, Gaurav; Arora, Sonali; Manocha, Sahil; Whalen, Sean

    2014-01-01

    Protein interaction networks are a promising type of data for studying complex biological systems. However, despite the rich information embedded in these networks, these networks face important data quality challenges of noise and incompleteness that adversely affect the results obtained from their analysis. Here, we apply a robust measure of local network structure called common neighborhood similarity (CNS) to address these challenges. Although several CNS measures have been proposed in the literature, an understanding of their relative efficacies for the analysis of interaction networks has been lacking. We follow the framework of graph transformation to convert the given interaction network into a transformed network corresponding to a variety of CNS measures evaluated. The effectiveness of each measure is then estimated by comparing the quality of protein function predictions obtained from its corresponding transformed network with those from the original network. Using a large set of human and fly protein interactions, and a set of over GO terms for both, we find that several of the transformed networks produce more accurate predictions than those obtained from the original network. In particular, the measure and other continuous CNS measures perform well this task, especially for large networks. Further investigation reveals that the two major factors contributing to this improvement are the abilities of CNS measures to prune out noisy edges and enhance functional coherence in the transformed networks. PMID:25275489

  8. Culex coronator in coastal Georgia and South Carolina.

    Science.gov (United States)

    Moulis, Robert A; Russell, Jennifer D; Lewandowski, Henry B; Thompson, Pamela S; Heusel, Jeffrey L

    2008-12-01

    In 2007, adult Culex coronator were collected in Chatham County, Georgia, and Jasper County, South Carolina, during nuisance and disease vector surveillance efforts. A total of 75 specimens of this species were collected at 8 widely separated locations in Chatham County, Georgia, and 4 closely situated sites in Jasper County, South Carolina. These represent the first Atlantic coastal records of this species in Georgia and the first confirmed records of Cx. coronator in South Carolina.

  9. Structural stability of interaction networks against negative external fields

    Science.gov (United States)

    Yoon, S.; Goltsev, A. V.; Mendes, J. F. F.

    2018-04-01

    We explore structural stability of weighted and unweighted networks of positively interacting agents against a negative external field. We study how the agents support the activity of each other to confront the negative field, which suppresses the activity of agents and can lead to collapse of the whole network. The competition between the interactions and the field shape the structure of stable states of the system. In unweighted networks (uniform interactions) the stable states have the structure of k -cores of the interaction network. The interplay between the topology and the distribution of weights (heterogeneous interactions) impacts strongly the structural stability against a negative field, especially in the case of fat-tailed distributions of weights. We show that apart from critical slowing down there is also a critical change in the system structure that precedes the network collapse. The change can serve as an early warning of the critical transition. To characterize changes of network structure we develop a method based on statistical analysis of the k -core organization and so-called "corona" clusters belonging to the k -cores.

  10. Report of a Planning Conference for Solar Technology Information Transfer in Georgia (Atlanta, Georgia, July 24-25, 1978).

    Science.gov (United States)

    Aldridge, Mark C., Ed.

    A summary of the deliberations of the Georgia planning conference of the Solar Technology Transfer Program is presented in this report. Topic areas include background information on the Georgia conference and a summary of the discussions and recommendations dealing with solar information transfer within state systems and the need for greater…

  11. Investigating physics learning with layered student interaction networks

    DEFF Research Database (Denmark)

    Bruun, Jesper; Traxler, Adrienne

    Centrality in student interaction networks (SINs) can be linked to variables like grades [1], persistence [2], and participation [3]. Recent efforts in the field of network science have been done to investigate layered - or multiplex - networks as mathematical objects [4]. These networks can be e......, this study investigates how target entropy [5,1] and pagerank [6,7] are affected when we take time and modes of interaction into account. We present our preliminary models and results and outline our future work in this area....

  12. Geological hazard monitoring system in Georgia

    Science.gov (United States)

    Gaprindashvili, George

    2017-04-01

    Georgia belongs to one of world's most complex mountainous regions according to the scale and frequency of Geological processes and damage caused to population, farmlands, and Infrastructure facilities. Geological hazards (landslide, debrisflow/mudflow, rockfall, erosion and etc.) are affecting many populated areas, agricultural fields, roads, oil and gas pipes, high-voltage electric power transmission towers, hydraulic structures, and tourist complexes. Landslides occur almost in all geomorphological zones, resulting in wide differentiation in the failure types and mechanisms and in the size-frequency distribution. In Georgia, geological hazards triggered by: 1. Activation of highly intense earthquakes; 2. Meteorological events provoking the disaster processes on the background of global climatic change; 3. Large-scale Human impact on the environment. The prediction and monitoring of Geological Hazards is a very wide theme, which involves different researchers from different spheres. Geological hazard monitoring is essential to prevent and mitigate these hazards. In past years in Georgia several monitoring system, such as Ground-based geodetic techniques, Debrisflow Early Warning System (EWS) were installed on high sensitive landslide and debrisflow areas. This work presents description of Geological hazard monitoring system in Georgia.

  13. Predicting and validating protein interactions using network structure.

    Directory of Open Access Journals (Sweden)

    Pao-Yang Chen

    2008-07-01

    Full Text Available Protein interactions play a vital part in the function of a cell. As experimental techniques for detection and validation of protein interactions are time consuming, there is a need for computational methods for this task. Protein interactions appear to form a network with a relatively high degree of local clustering. In this paper we exploit this clustering by suggesting a score based on triplets of observed protein interactions. The score utilises both protein characteristics and network properties. Our score based on triplets is shown to complement existing techniques for predicting protein interactions, outperforming them on data sets which display a high degree of clustering. The predicted interactions score highly against test measures for accuracy. Compared to a similar score derived from pairwise interactions only, the triplet score displays higher sensitivity and specificity. By looking at specific examples, we show how an experimental set of interactions can be enriched and validated. As part of this work we also examine the effect of different prior databases upon the accuracy of prediction and find that the interactions from the same kingdom give better results than from across kingdoms, suggesting that there may be fundamental differences between the networks. These results all emphasize that network structure is important and helps in the accurate prediction of protein interactions. The protein interaction data set and the program used in our analysis, and a list of predictions and validations, are available at http://www.stats.ox.ac.uk/bioinfo/resources/PredictingInteractions.

  14. Evidence of probabilistic behaviour in protein interaction networks

    Directory of Open Access Journals (Sweden)

    Reifman Jaques

    2008-01-01

    Full Text Available Abstract Background Data from high-throughput experiments of protein-protein interactions are commonly used to probe the nature of biological organization and extract functional relationships between sets of proteins. What has not been appreciated is that the underlying mechanisms involved in assembling these networks may exhibit considerable probabilistic behaviour. Results We find that the probability of an interaction between two proteins is generally proportional to the numerical product of their individual interacting partners, or degrees. The degree-weighted behaviour is manifested throughout the protein-protein interaction networks studied here, except for the high-degree, or hub, interaction areas. However, we find that the probabilities of interaction between the hubs are still high. Further evidence is provided by path length analyses, which show that these hubs are separated by very few links. Conclusion The results suggest that protein-protein interaction networks incorporate probabilistic elements that lead to scale-rich hierarchical architectures. These observations seem to be at odds with a biologically-guided organization. One interpretation of the findings is that we are witnessing the ability of proteins to indiscriminately bind rather than the protein-protein interactions that are actually utilized by the cell in biological processes. Therefore, the topological study of a degree-weighted network requires a more refined methodology to extract biological information about pathways, modules, or other inferred relationships among proteins.

  15. Prediction and characterization of protein-protein interaction networks in swine

    Directory of Open Access Journals (Sweden)

    Wang Fen

    2012-01-01

    Full Text Available Abstract Background Studying the large-scale protein-protein interaction (PPI network is important in understanding biological processes. The current research presents the first PPI map of swine, which aims to give new insights into understanding their biological processes. Results We used three methods, Interolog-based prediction of porcine PPI network, domain-motif interactions from structural topology-based prediction of porcine PPI network and motif-motif interactions from structural topology-based prediction of porcine PPI network, to predict porcine protein interactions among 25,767 porcine proteins. We predicted 20,213, 331,484, and 218,705 porcine PPIs respectively, merged the three results into 567,441 PPIs, constructed four PPI networks, and analyzed the topological properties of the porcine PPI networks. Our predictions were validated with Pfam domain annotations and GO annotations. Averages of 70, 10,495, and 863 interactions were related to the Pfam domain-interacting pairs in iPfam database. For comparison, randomized networks were generated, and averages of only 4.24, 66.79, and 44.26 interactions were associated with Pfam domain-interacting pairs in iPfam database. In GO annotations, we found 52.68%, 75.54%, 27.20% of the predicted PPIs sharing GO terms respectively. However, the number of PPI pairs sharing GO terms in the 10,000 randomized networks reached 52.68%, 75.54%, 27.20% is 0. Finally, we determined the accuracy and precision of the methods. The methods yielded accuracies of 0.92, 0.53, and 0.50 at precisions of about 0.93, 0.74, and 0.75, respectively. Conclusion The results reveal that the predicted PPI networks are considerably reliable. The present research is an important pioneering work on protein function research. The porcine PPI data set, the confidence score of each interaction and a list of related data are available at (http://pppid.biositemap.com/.

  16. Genetic diversity, virulence, and Meloidogyne incognita interactions of Fusarium oxysporum isolates causing cotton wilt in Georgia

    Science.gov (United States)

    Locally severe outbreaks of Fusarium wilt of cotton (Gossypium spp.) in South Georgia raised concerns about the genotypes of the causal pathogen, Fusarium oxysporum f. sp. vasinfectum. Vegetative complementation tests and DNA sequence analysis were used to determine genetic diversity among 492 F. ox...

  17. Unveiling protein functions through the dynamics of the interaction network.

    Directory of Open Access Journals (Sweden)

    Irene Sendiña-Nadal

    Full Text Available Protein interaction networks have become a tool to study biological processes, either for predicting molecular functions or for designing proper new drugs to regulate the main biological interactions. Furthermore, such networks are known to be organized in sub-networks of proteins contributing to the same cellular function. However, the protein function prediction is not accurate and each protein has traditionally been assigned to only one function by the network formalism. By considering the network of the physical interactions between proteins of the yeast together with a manual and single functional classification scheme, we introduce a method able to reveal important information on protein function, at both micro- and macro-scale. In particular, the inspection of the properties of oscillatory dynamics on top of the protein interaction network leads to the identification of misclassification problems in protein function assignments, as well as to unveil correct identification of protein functions. We also demonstrate that our approach can give a network representation of the meta-organization of biological processes by unraveling the interactions between different functional classes.

  18. Building a glaucoma interaction network using a text mining approach.

    Science.gov (United States)

    Soliman, Maha; Nasraoui, Olfa; Cooper, Nigel G F

    2016-01-01

    The volume of biomedical literature and its underlying knowledge base is rapidly expanding, making it beyond the ability of a single human being to read through all the literature. Several automated methods have been developed to help make sense of this dilemma. The present study reports on the results of a text mining approach to extract gene interactions from the data warehouse of published experimental results which are then used to benchmark an interaction network associated with glaucoma. To the best of our knowledge, there is, as yet, no glaucoma interaction network derived solely from text mining approaches. The presence of such a network could provide a useful summative knowledge base to complement other forms of clinical information related to this disease. A glaucoma corpus was constructed from PubMed Central and a text mining approach was applied to extract genes and their relations from this corpus. The extracted relations between genes were checked using reference interaction databases and classified generally as known or new relations. The extracted genes and relations were then used to construct a glaucoma interaction network. Analysis of the resulting network indicated that it bears the characteristics of a small world interaction network. Our analysis showed the presence of seven glaucoma linked genes that defined the network modularity. A web-based system for browsing and visualizing the extracted glaucoma related interaction networks is made available at http://neurogene.spd.louisville.edu/GlaucomaINViewer/Form1.aspx. This study has reported the first version of a glaucoma interaction network using a text mining approach. The power of such an approach is in its ability to cover a wide range of glaucoma related studies published over many years. Hence, a bigger picture of the disease can be established. To the best of our knowledge, this is the first glaucoma interaction network to summarize the known literature. The major findings were a set of

  19. Flood-tracking chart for the Withlacoochee and Little River Basins in south-central Georgia and northern Florida

    Science.gov (United States)

    Gotvald, Anthony J.; McCallum, Brian E.; Painter, Jaime A.

    2014-01-01

    The U.S. Geological Survey (USGS), in cooperation with other Federal, State, and local agencies, operates a flood-monitoring system in the Withlacoochee and Little River Basins. This system is a network of automated river stage stations (ten are shown on page 2 of this publication) that transmit stage data through satellite telemetry to the USGS in Atlanta, Georgia and the National Weather Service (NWS) in Peachtree City, Georgia. During floods, the public and emergency response agencies use this information to make decisions about road closures, evacuations, and other public safety issues. This Withlacoochee and Little River Basins flood-tracking chart can be used by local citizens and emergency response personnel to record the latest river stage and predicted flood-crest information along the Withlacoochee River, Little River, and Okapilco Creek in south-central Georgia and northern Florida. By comparing the current stage (water-surface level above a datum) and predicted flood crest to the recorded peak stages of previous floods, emergency response personnel and residents can make informed decisions concerning the threat to life and property.

  20. Default network modulation and large-scale network interactivity in healthy young and old adults.

    Science.gov (United States)

    Spreng, R Nathan; Schacter, Daniel L

    2012-11-01

    We investigated age-related changes in default, attention, and control network activity and their interactions in young and old adults. Brain activity during autobiographical and visuospatial planning was assessed using multivariate analysis and with intrinsic connectivity networks as regions of interest. In both groups, autobiographical planning engaged the default network while visuospatial planning engaged the attention network, consistent with a competition between the domains of internalized and externalized cognition. The control network was engaged for both planning tasks. In young subjects, the control network coupled with the default network during autobiographical planning and with the attention network during visuospatial planning. In old subjects, default-to-control network coupling was observed during both planning tasks, and old adults failed to deactivate the default network during visuospatial planning. This failure is not indicative of default network dysfunction per se, evidenced by default network engagement during autobiographical planning. Rather, a failure to modulate the default network in old adults is indicative of a lower degree of flexible network interactivity and reduced dynamic range of network modulation to changing task demands.

  1. Human cancer protein-protein interaction network: a structural perspective.

    Directory of Open Access Journals (Sweden)

    Gozde Kar

    2009-12-01

    Full Text Available Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network. The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%. We illustrate the interface related affinity properties of two cancer-related hub

  2. Development of Novel Random Network Theory-Based Approaches to Identify Network Interactions among Nitrifying Bacteria

    Energy Technology Data Exchange (ETDEWEB)

    Shi, Cindy

    2015-07-17

    The interactions among different microbial populations in a community could play more important roles in determining ecosystem functioning than species numbers and their abundances, but very little is known about such network interactions at a community level. The goal of this project is to develop novel framework approaches and associated software tools to characterize the network interactions in microbial communities based on high throughput, large scale high-throughput metagenomics data and apply these approaches to understand the impacts of environmental changes (e.g., climate change, contamination) on network interactions among different nitrifying populations and associated microbial communities.

  3. A Failed Experiment: Georgia's Tax Credit Scholarships for Private Schools

    Science.gov (United States)

    Southern Education Foundation, 2011

    2011-01-01

    Georgia is one of seven states that currently allow tax credits for scholarships to private schools. Georgia's law was enacted in May 2008 in order to assist low income students to transfer out of low performing public schools. Operations under the new act began in late 2008. The law permits taxpayers in Georgia to reduce their annual state taxes…

  4. Empirical evaluation of neutral interactions in host-parasite networks.

    Science.gov (United States)

    Canard, E F; Mouquet, N; Mouillot, D; Stanko, M; Miklisova, D; Gravel, D

    2014-04-01

    While niche-based processes have been invoked extensively to explain the structure of interaction networks, recent studies propose that neutrality could also be of great importance. Under the neutral hypothesis, network structure would simply emerge from random encounters between individuals and thus would be directly linked to species abundance. We investigated the impact of species abundance distributions on qualitative and quantitative metrics of 113 host-parasite networks. We analyzed the concordance between neutral expectations and empirical observations at interaction, species, and network levels. We found that species abundance accurately predicts network metrics at all levels. Despite host-parasite systems being constrained by physiology and immunology, our results suggest that neutrality could also explain, at least partially, their structure. We hypothesize that trait matching would determine potential interactions between species, while abundance would determine their realization.

  5. Speech networks at rest and in action: interactions between functional brain networks controlling speech production

    Science.gov (United States)

    Fuertinger, Stefan

    2015-01-01

    Speech production is one of the most complex human behaviors. Although brain activation during speaking has been well investigated, our understanding of interactions between the brain regions and neural networks remains scarce. We combined seed-based interregional correlation analysis with graph theoretical analysis of functional MRI data during the resting state and sentence production in healthy subjects to investigate the interface and topology of functional networks originating from the key brain regions controlling speech, i.e., the laryngeal/orofacial motor cortex, inferior frontal and superior temporal gyri, supplementary motor area, cingulate cortex, putamen, and thalamus. During both resting and speaking, the interactions between these networks were bilaterally distributed and centered on the sensorimotor brain regions. However, speech production preferentially recruited the inferior parietal lobule (IPL) and cerebellum into the large-scale network, suggesting the importance of these regions in facilitation of the transition from the resting state to speaking. Furthermore, the cerebellum (lobule VI) was the most prominent region showing functional influences on speech-network integration and segregation. Although networks were bilaterally distributed, interregional connectivity during speaking was stronger in the left vs. right hemisphere, which may have underlined a more homogeneous overlap between the examined networks in the left hemisphere. Among these, the laryngeal motor cortex (LMC) established a core network that fully overlapped with all other speech-related networks, determining the extent of network interactions. Our data demonstrate complex interactions of large-scale brain networks controlling speech production and point to the critical role of the LMC, IPL, and cerebellum in the formation of speech production network. PMID:25673742

  6. Deciphering microbial interactions and detecting keystone species with co-occurrence networks

    Directory of Open Access Journals (Sweden)

    David eBerry

    2014-05-01

    Full Text Available Co-occurrence networks produced from microbial survey sequencing data are frequently used to identify interactions between community members. While this approach has potential to reveal ecological processes, it has been insufficiently validated due to the technical limitations inherent in studying complex microbial ecosystems. Here, we simulate multi-species microbial communities with known interaction patterns using generalized Lotka-Volterra dynamics, construct co-occurrence networks, and evaluate how well networks reveal the underlying interactions, and how experimental and ecological parameters can affect network inference and interpretation. We find that co-occurrence networks can recapitulate interaction networks under certain conditions, but that they lose interpretability when the effects of habitat filtering become significant. We demonstrate that networks suffer from local hot spots of spurious correlation in the neighborhood of hub species that engage in many interactions. We also identify topological features associated with keystone species in co-occurrence networks. This study provides a substantiated framework to guide environmental microbiologists in the construction and interpretation of co-occurrence networks from microbial survey datasets.

  7. Deciphering microbial interactions and detecting keystone species with co-occurrence networks.

    Science.gov (United States)

    Berry, David; Widder, Stefanie

    2014-01-01

    Co-occurrence networks produced from microbial survey sequencing data are frequently used to identify interactions between community members. While this approach has potential to reveal ecological processes, it has been insufficiently validated due to the technical limitations inherent in studying complex microbial ecosystems. Here, we simulate multi-species microbial communities with known interaction patterns using generalized Lotka-Volterra dynamics. We then construct co-occurrence networks and evaluate how well networks reveal the underlying interactions and how experimental and ecological parameters can affect network inference and interpretation. We find that co-occurrence networks can recapitulate interaction networks under certain conditions, but that they lose interpretability when the effects of habitat filtering become significant. We demonstrate that networks suffer from local hot spots of spurious correlation in the neighborhood of hub species that engage in many interactions. We also identify topological features associated with keystone species in co-occurrence networks. This study provides a substantiated framework to guide environmental microbiologists in the construction and interpretation of co-occurrence networks from microbial survey datasets.

  8. Establishing control over nuclear materials and radiation sources in Georgia

    International Nuclear Information System (INIS)

    Basilia, G.

    2010-01-01

    Regulatory control over radiation sources in Georgia was lost after disintegration of the Soviet Union. A number of radiation accidents and illegal events occurred in Georgia. From 1999 Nuclear and Radiation Safety Service of the Ministry of Environmental Protection and Natural Resources is responsible for regulatory control over radiation sources in Georgia. US NRC Regulatory Assistance Program in Georgia Assist the Service in establishing long term regulatory control over sources. Main focuses of US NRC program are country-wide inventory, create National Registry of sources, safe storage of disused sources, upgrade legislation and regulation, implementation licensing and inspection activities

  9. End of Interactive Emailing from the Technical Network

    CERN Multimedia

    2006-01-01

    According to the CNIC Security Policy for Control Systems (EDMS #584092), interactive emailing on PCs (and other devices) connected to the Technical Network is prohibited. Please note that from November 6th, neither reading emails nor sending emails interactively using e.g. Outlook or Pine mail clients on PCs connected to the Technical Network will be possible anymore. However, automatically generated emails will not be blocked and can still be sent off using CERNMX.CERN.CH as mail server. These restrictions DO NOT apply to PCs connected to any other network, like the General Purpose (or office) network. If you have questions, please do not hesitate to contact Uwe Epting, Pierre Charrue or Stefan Lueders (Technical-Network.Administrator@cern.ch). Your CNIC Working Group

  10. Prediction of Protein-Protein Interactions Related to Protein Complexes Based on Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Peng Liu

    2015-01-01

    Full Text Available A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.

  11. Cluster Approach to Network Interaction in Pedagogical University

    Science.gov (United States)

    Chekaleva, Nadezhda V.; Makarova, Natalia S.; Drobotenko, Yulia B.

    2016-01-01

    The study presented in the article is devoted to the analysis of theory and practice of network interaction within the framework of education clusters. Education clusters are considered to be a novel form of network interaction in pedagogical education in Russia. The aim of the article is to show the advantages and disadvantages of the cluster…

  12. Network traffic intelligence using a low interaction honeypot

    Science.gov (United States)

    Nyamugudza, Tendai; Rajasekar, Venkatesh; Sen, Prasad; Nirmala, M.; Madhu Viswanatham, V.

    2017-11-01

    Advancements in networking technology have seen more and more devices becoming connected day by day. This has given organizations capacity to extend their networks beyond their boundaries to remote offices and remote employees. However as the network grows security becomes a major challenge since the attack surface also increases. There is need to guard the network against different types of attacks like intrusion and malware through using different tools at different networking levels. This paper describes how network intelligence can be acquired through implementing a low-interaction honeypot which detects and track network intrusion. Honeypot allows an organization to interact and gather information about an attack earlier before it compromises the network. This process is important because it allows the organization to learn about future attacks of the same nature and allows them to develop counter measures. The paper further shows how honeypot-honey net based model for interruption detection system (IDS) can be used to get the best valuable information about the attacker and prevent unexpected harm to the network.

  13. A scored human protein-protein interaction network to catalyze genomic interpretation

    DEFF Research Database (Denmark)

    Li, Taibo; Wernersson, Rasmus; Hansen, Rasmus B

    2017-01-01

    Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb_InBioMap,......Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (In...

  14. Energy balance of Georgia

    Directory of Open Access Journals (Sweden)

    Demur Chomakhidze

    2016-09-01

    It is shown that, traditionally, the energy balance of Georgia is in deep deficit. The suggestions for its improvement are provided in the Article. The country imports almost all amount of oil and natural gas. Electricity balance is relatively stable. In the recent years, some amount of electricity is exported to the neighboring countries. Generally, the country satisfies only 30–35% of own energy consumption by local generation, and the rest amount of resources are imported from abroad. The reason of deficit to some extent is irrational and wasteful consumption of energy resources. The article examines the organizational difficulties in drawing up energy balance of Georgia and statistical problems of recording of energy production and consumption at the initial stage of market economy.

  15. Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae

    Science.gov (United States)

    Reguly, Teresa; Breitkreutz, Ashton; Boucher, Lorrie; Breitkreutz, Bobby-Joe; Hon, Gary C; Myers, Chad L; Parsons, Ainslie; Friesen, Helena; Oughtred, Rose; Tong, Amy; Stark, Chris; Ho, Yuen; Botstein, David; Andrews, Brenda; Boone, Charles; Troyanskya, Olga G; Ideker, Trey; Dolinski, Kara; Batada, Nizar N; Tyers, Mike

    2006-01-01

    Background The study of complex biological networks and prediction of gene function has been enabled by high-throughput (HTP) methods for detection of genetic and protein interactions. Sparse coverage in HTP datasets may, however, distort network properties and confound predictions. Although a vast number of well substantiated interactions are recorded in the scientific literature, these data have not yet been distilled into networks that enable system-level inference. Results We describe here a comprehensive database of genetic and protein interactions, and associated experimental evidence, for the budding yeast Saccharomyces cerevisiae, as manually curated from over 31,793 abstracts and online publications. This literature-curated (LC) dataset contains 33,311 interactions, on the order of all extant HTP datasets combined. Surprisingly, HTP protein-interaction datasets currently achieve only around 14% coverage of the interactions in the literature. The LC network nevertheless shares attributes with HTP networks, including scale-free connectivity and correlations between interactions, abundance, localization, and expression. We find that essential genes or proteins are enriched for interactions with other essential genes or proteins, suggesting that the global network may be functionally unified. This interconnectivity is supported by a substantial overlap of protein and genetic interactions in the LC dataset. We show that the LC dataset considerably improves the predictive power of network-analysis approaches. The full LC dataset is available at the BioGRID () and SGD () databases. Conclusion Comprehensive datasets of biological interactions derived from the primary literature provide critical benchmarks for HTP methods, augment functional prediction, and reveal system-level attributes of biological networks. PMID:16762047

  16. Online networks, social interaction and segregation: An evolutionary approach

    OpenAIRE

    Antoci, Angelo; Sabatini, Fabio

    2018-01-01

    There is growing evidence that face-to-face interaction is declining in many countries, exacerbating the phenomenon of social isolation. On the other hand, social interaction through online networking sites is steeply rising. To analyze these societal dynamics, we have built an evolutionary game model in which agents can choose between three strategies of social participation: 1) interaction via both online social networks and face-to-face encounters; 2) interaction by exclusive means of face...

  17. Influences of brain development and ageing on cortical interactive networks.

    Science.gov (United States)

    Zhu, Chengyu; Guo, Xiaoli; Jin, Zheng; Sun, Junfeng; Qiu, Yihong; Zhu, Yisheng; Tong, Shanbao

    2011-02-01

    To study the effect of brain development and ageing on the pattern of cortical interactive networks. By causality analysis of multichannel electroencephalograph (EEG) with partial directed coherence (PDC), we investigated the different neural networks involved in the whole cortex as well as the anterior and posterior areas in three age groups, i.e., children (0-10 years), mid-aged adults (26-38 years) and the elderly (56-80 years). By comparing the cortical interactive networks in different age groups, the following findings were concluded: (1) the cortical interactive network in the right hemisphere develops earlier than its left counterpart in the development stage; (2) the cortical interactive network of anterior cortex, especially at C3 and F3, is demonstrated to undergo far more extensive changes, compared with the posterior area during brain development and ageing; (3) the asymmetry of the cortical interactive networks declines during ageing with more loss of connectivity in the left frontal and central areas. The age-related variation of cortical interactive networks from resting EEG provides new insights into brain development and ageing. Our findings demonstrated that the PDC analysis of EEG is a powerful approach for characterizing the cortical functional connectivity during brain development and ageing. Copyright © 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  18. Dynamics of Moment Neuronal Networks with Intra- and Inter-Interactions

    Directory of Open Access Journals (Sweden)

    Xuyan Xiang

    2015-01-01

    Full Text Available A framework of moment neuronal networks with intra- and inter-interactions is presented. It is to show how the spontaneous activity is propagated across the homogeneous and heterogeneous network. The input-output firing relationship and the stability are first explored for a homogeneous network. For heterogeneous network without the constraint of the correlation coefficients between neurons, a more sophisticated dynamics is then explored. With random interactions, the network gets easily synchronized. However, desynchronization is produced by a lateral interaction such as Mexico hat function. It is the external intralayer input unit that offers a more sophisticated and unexpected dynamics over the predecessors. Hence, the work further opens up the possibility of carrying out a stochastic computation in neuronal networks.

  19. 40 CFR 81.237 - Northeast Georgia Intrastate Air Quality Control Region.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 17 2010-07-01 2010-07-01 false Northeast Georgia Intrastate Air... Air Quality Control Regions § 81.237 Northeast Georgia Intrastate Air Quality Control Region. The Northeast Georgia Intrastate Air Quality Control Region consists of the territorial area encompassed by the...

  20. Speech networks at rest and in action: interactions between functional brain networks controlling speech production.

    Science.gov (United States)

    Simonyan, Kristina; Fuertinger, Stefan

    2015-04-01

    Speech production is one of the most complex human behaviors. Although brain activation during speaking has been well investigated, our understanding of interactions between the brain regions and neural networks remains scarce. We combined seed-based interregional correlation analysis with graph theoretical analysis of functional MRI data during the resting state and sentence production in healthy subjects to investigate the interface and topology of functional networks originating from the key brain regions controlling speech, i.e., the laryngeal/orofacial motor cortex, inferior frontal and superior temporal gyri, supplementary motor area, cingulate cortex, putamen, and thalamus. During both resting and speaking, the interactions between these networks were bilaterally distributed and centered on the sensorimotor brain regions. However, speech production preferentially recruited the inferior parietal lobule (IPL) and cerebellum into the large-scale network, suggesting the importance of these regions in facilitation of the transition from the resting state to speaking. Furthermore, the cerebellum (lobule VI) was the most prominent region showing functional influences on speech-network integration and segregation. Although networks were bilaterally distributed, interregional connectivity during speaking was stronger in the left vs. right hemisphere, which may have underlined a more homogeneous overlap between the examined networks in the left hemisphere. Among these, the laryngeal motor cortex (LMC) established a core network that fully overlapped with all other speech-related networks, determining the extent of network interactions. Our data demonstrate complex interactions of large-scale brain networks controlling speech production and point to the critical role of the LMC, IPL, and cerebellum in the formation of speech production network. Copyright © 2015 the American Physiological Society.

  1. DyNet: visualization and analysis of dynamic molecular interaction networks.

    Science.gov (United States)

    Goenawan, Ivan H; Bryan, Kenneth; Lynn, David J

    2016-09-01

    : The ability to experimentally determine molecular interactions on an almost proteome-wide scale under different conditions is enabling researchers to move from static to dynamic network analysis, uncovering new insights into how interaction networks are physically rewired in response to different stimuli and in disease. Dynamic interaction data presents a special challenge in network biology. Here, we present DyNet, a Cytoscape application that provides a range of functionalities for the visualization, real-time synchronization and analysis of large multi-state dynamic molecular interaction networks enabling users to quickly identify and analyze the most 'rewired' nodes across many network states. DyNet is available at the Cytoscape (3.2+) App Store (http://apps.cytoscape.org/apps/dynet). david.lynn@sahmri.com Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  2. Myths on Bi-direction Communication of Web 2.0 Based Social Networks: Is Social Network Truly Interactive?

    Science.gov (United States)

    2011-03-10

    more and more social interactions are happening on the on-line. Especially recent uptake of the social network sites (SNSs), such as Facebook (http...Smart phones • Live updates within social networks • Facebook & Twitters Solution: WebMon for Risk Management Need for New WebMon for Social Networks ...Title: Myths on bi-direction communication of Web 2.0 based social networks : Is social network truly interactive

  3. Temporal stability in human interaction networks

    Science.gov (United States)

    Fabbri, Renato; Fabbri, Ricardo; Antunes, Deborah Christina; Pisani, Marilia Mello; de Oliveira, Osvaldo Novais

    2017-11-01

    This paper reports on stable (or invariant) properties of human interaction networks, with benchmarks derived from public email lists. Activity, recognized through messages sent, along time and topology were observed in snapshots in a timeline, and at different scales. Our analysis shows that activity is practically the same for all networks across timescales ranging from seconds to months. The principal components of the participants in the topological metrics space remain practically unchanged as different sets of messages are considered. The activity of participants follows the expected scale-free trace, thus yielding the hub, intermediary and peripheral classes of vertices by comparison against the Erdös-Rényi model. The relative sizes of these three sectors are essentially the same for all email lists and the same along time. Typically, 45% are peripheral vertices. Similar results for the distribution of participants in the three sectors and for the relative importance of the topological metrics were obtained for 12 additional networks from Facebook, Twitter and ParticipaBR. These properties are consistent with the literature and may be general for human interaction networks, which has important implications for establishing a typology of participants based on quantitative criteria.

  4. Integrated multimedia information system on interactive CATV network

    Science.gov (United States)

    Lee, Meng-Huang; Chang, Shin-Hung

    1998-10-01

    In the current CATV system architectures, they provide one- way delivery of a common menu of entertainment to all the homes through the cable network. Through the technologies evolution, the interactive services (or two-way services) can be provided in the cable TV systems. They can supply customers with individualized programming and support real- time two-way communications. With a view to the service type changed from the one-way delivery systems to the two-way interactive systems, `on demand services' is a distinct feature of multimedia systems. In this paper, we present our work of building up an integrated multimedia system on interactive CATV network in Shih Chien University. Besides providing the traditional analog TV programming from the cable operator, we filter some channels to reserve them as our campus information channels. In addition to the analog broadcasting channel, the system also provides the interactive digital multimedia services, e.g. Video-On- Demand (VOD), Virtual Reality, BBS, World-Wide-Web, and Internet Radio Station. These two kinds of services are integrated in a CATV network by the separation of frequency allocation for the analog broadcasting service and the digital interactive services. Our ongoing work is to port our previous work of building up a VOD system conformed to DAVIC standard (for inter-operability concern) on Ethernet network into the current system.

  5. Vulnerability of networks of interacting Markov chains.

    Science.gov (United States)

    Kocarev, L; Zlatanov, N; Trajanov, D

    2010-05-13

    The concept of vulnerability is introduced for a model of random, dynamical interactions on networks. In this model, known as the influence model, the nodes are arranged in an arbitrary network, while the evolution of the status at a node is according to an internal Markov chain, but with transition probabilities that depend not only on the current status of that node but also on the statuses of the neighbouring nodes. Vulnerability is treated analytically and numerically for several networks with different topological structures, as well as for two real networks--the network of infrastructures and the EU power grid--identifying the most vulnerable nodes of these networks.

  6. Bayesian network model for identification of pathways by integrating protein interaction with genetic interaction data.

    Science.gov (United States)

    Fu, Changhe; Deng, Su; Jin, Guangxu; Wang, Xinxin; Yu, Zu-Guo

    2017-09-21

    Molecular interaction data at proteomic and genetic levels provide physical and functional insights into a molecular biosystem and are helpful for the construction of pathway structures complementarily. Despite advances in inferring biological pathways using genetic interaction data, there still exists weakness in developed models, such as, activity pathway networks (APN), when integrating the data from proteomic and genetic levels. It is necessary to develop new methods to infer pathway structure by both of interaction data. We utilized probabilistic graphical model to develop a new method that integrates genetic interaction and protein interaction data and infers exquisitely detailed pathway structure. We modeled the pathway network as Bayesian network and applied this model to infer pathways for the coherent subsets of the global genetic interaction profiles, and the available data set of endoplasmic reticulum genes. The protein interaction data were derived from the BioGRID database. Our method can accurately reconstruct known cellular pathway structures, including SWR complex, ER-Associated Degradation (ERAD) pathway, N-Glycan biosynthesis pathway, Elongator complex, Retromer complex, and Urmylation pathway. By comparing N-Glycan biosynthesis pathway and Urmylation pathway identified from our approach with that from APN, we found that our method is able to overcome its weakness (certain edges are inexplicable). According to underlying protein interaction network, we defined a simple scoring function that only adopts genetic interaction information to avoid the balance difficulty in the APN. Using the effective stochastic simulation algorithm, the performance of our proposed method is significantly high. We developed a new method based on Bayesian network to infer detailed pathway structures from interaction data at proteomic and genetic levels. The results indicate that the developed method performs better in predicting signaling pathways than previously

  7. Interacting neural networks

    Science.gov (United States)

    Metzler, R.; Kinzel, W.; Kanter, I.

    2000-08-01

    Several scenarios of interacting neural networks which are trained either in an identical or in a competitive way are solved analytically. In the case of identical training each perceptron receives the output of its neighbor. The symmetry of the stationary state as well as the sensitivity to the used training algorithm are investigated. Two competitive perceptrons trained on mutually exclusive learning aims and a perceptron which is trained on the opposite of its own output are examined analytically. An ensemble of competitive perceptrons is used as decision-making algorithms in a model of a closed market (El Farol Bar problem or the Minority Game. In this game, a set of agents who have to make a binary decision is considered.); each network is trained on the history of minority decisions. This ensemble of perceptrons relaxes to a stationary state whose performance can be better than random.

  8. USE OF COMPLEMENTARY AND ALTERNATIVE MEDICINE IN GEORGIA.

    Science.gov (United States)

    Nadareishvili, I; Lunze, K; Tabagari, N; Beraia, A; Pkhakadze, G

    2017-11-01

    In Georgia, like in most countries globally, people commonly resort to complementary and alternative medicine (CAM). However, not much is known about CAM practices there. The aim of the study was to document common practices of CAM in Georgia and related patient attitudes. We collected data from peoples who commonly use CAM at 20 service provision centers in Georgia using cluster sampling from 300 patients. We admininstered a cross-sectional survey and conducted descriptive statistical analyses. People in Georgia use CAM either for prevention to improve general health (33%) or to treat chronic conditions (36%), spending about 25 Euros per month out of pocket. Most (77%) get their knowledge about CAM from family or friends , less than half (44%) from books or media, and 11% from medical providers. A close person's advice or experience was the most common rationale given for CAM use (54%). In our sample, 17% either don't trust or are unsatisfied with conventional medicine, 29% found CAM treatment "very effective" and 61% "quite/partially" effective; only 5% not effective. Conventional treatment was stopped in half of the cases. 35% of respondents informed their physicians of their CAM use, while about half did not. Public mistrust towards conventional medicine, CAM user high satisfaction, relatively low cost of such services in Georgia - are the factors letting us to suggest that CAM use will further increase. Frequent self taking decisions made by patients to stop physician prescribed treatment, not informing physicians on CAM use, as well as other factors put patients health at risk. Further research and capacity building in practice, education and other related aspects are needed to establish evidence-based regulation and standards for CAM in Georgia that ensure informed decision making and patient safety.

  9. Semantic integration to identify overlapping functional modules in protein interaction networks

    Directory of Open Access Journals (Sweden)

    Ramanathan Murali

    2007-07-01

    Full Text Available Abstract Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification.

  10. Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections

    Science.gov (United States)

    de Vos, Marjon G. J.; Bollenbach, Tobias

    2017-01-01

    Polymicrobial infections constitute small ecosystems that accommodate several bacterial species. Commonly, these bacteria are investigated in isolation. However, it is unknown to what extent the isolates interact and whether their interactions alter bacterial growth and ecosystem resilience in the presence and absence of antibiotics. We quantified the complete ecological interaction network for 72 bacterial isolates collected from 23 individuals diagnosed with polymicrobial urinary tract infections and found that most interactions cluster based on evolutionary relatedness. Statistical network analysis revealed that competitive and cooperative reciprocal interactions are enriched in the global network, while cooperative interactions are depleted in the individual host community networks. A population dynamics model parameterized by our measurements suggests that interactions restrict community stability, explaining the observed species diversity of these communities. We further show that the clinical isolates frequently protect each other from clinically relevant antibiotics. Together, these results highlight that ecological interactions are crucial for the growth and survival of bacteria in polymicrobial infection communities and affect their assembly and resilience. PMID:28923953

  11. Integrated mined-area reclamation and land-use planning. Volume 3C. A case study of surface mining and reclamation planning: Georgia Kaolin Company Clay Mines, Washington County, Georgia

    Energy Technology Data Exchange (ETDEWEB)

    Guernsey, J L; Brown, L A; Perry, A O

    1978-02-01

    This case study examines the reclamation practices of the Georgia Kaolin's American Industrial Clay Company Division, a kaolin producer centered in Twiggs, Washington, and Wilkinson Counties, Georgia. The State of Georgia accounts for more than one-fourth of the world's kaolin production and about three-fourths of U.S. kaolin output. The mining of kaolin in Georgia illustrates the effects of mining and reclaiming lands disturbed by area surface mining. The disturbed areas are reclaimed under the rules and regulations of the Georgia Surface Mining Act of 1968. The natural conditions influencing the reclamation methodologies and techniques are markedly unique from those of other mining operations. The environmental disturbances and procedures used in reclaiming the kaolin mined lands are reviewed and implications for planners are noted.

  12. Corruption Risks of Private Tutoring: Case of Georgia

    Science.gov (United States)

    Kobakhidze, Magda Nutsa

    2014-01-01

    The paper focuses on teacher-supplied private tutoring in the context of post-Soviet Georgia, and elucidates the ways in which teacher-supplied private tutoring can be related to educational corruption. The paper draws on data from in-depth interviews of 18 school teachers in different parts of Georgia in 2013. The findings of the qualitative…

  13. "Explaining the Gender Wage Gap in Georgia"

    OpenAIRE

    Tamar Khitarishvili

    2009-01-01

    This paper evaluates gender wage differentials in Georgia between 2000 and 2004. Using ordinary least squares, we find that the gender wage gap in Georgia is substantially higher than in other transition countries. Correcting for sample selection bias using the Heckman approach further increases the gender wage gap. The Blinder Oaxaca decomposition results suggest that most of the wage gap remains unexplained. The explained portion of the gap is almost entirely attributed to industrial variab...

  14. Functional modules by relating protein interaction networks and gene expression.

    Science.gov (United States)

    Tornow, Sabine; Mewes, H W

    2003-11-01

    Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

  15. NatalieQ: A web server for protein-protein interaction network querying

    NARCIS (Netherlands)

    El-Kebir, M.; Brandt, B.W.; Heringa, J.; Klau, G.W.

    2014-01-01

    Background Molecular interactions need to be taken into account to adequately model the complex behavior of biological systems. These interactions are captured by various types of biological networks, such as metabolic, gene-regulatory, signal transduction and protein-protein interaction networks.

  16. Network Interactions in the Great Altai Region

    Directory of Open Access Journals (Sweden)

    Lev Aleksandrovich Korshunov

    2017-12-01

    Full Text Available To improve the efficiency and competitiveness of the regional economy, an effective interaction between educational institutions in the Great Altai region is needed. The innovation growth can enhancing this interaction. The article explores the state of network structures in the economy and higher education in the border territories of the countries of Great Altai. The authors propose an updated approach to the three-level classification of network interaction. We analyze growing influence of the countries with emerging economies. We define the factors that impede the more stable and multifaceted regional development of these countries. Further, the authors determine indicators of the higher education systems and cooperation systems at the university level between the Shanghai Cooperation Organization countries (SCO and BRICS countries, showing the international rankings of the universities in these countries. The teaching language is important to overcome the obstacles in the interregional cooperation. The authors specify the problems of the development of the universities of the SCO and BRICS countries as global educational networks. The research applies basic scientific logical methods of analysis and synthesis, induction and deduction, as well as the SWOT analysis method. We have indentified and analyzed the existing economic and educational relations. To promote the economic innovation development of the border territories of the Great Altai, we propose a model of regional network university. Modern universities function in a new economic environment. Thus, in a great extent, they form the technological and social aspects of this environment. Innovative network structures contribute to the formation of a new network institutional environment of the regional economy, which impacts the macro- and microeconomic performance of the region as a whole. The results of the research can help to optimize the regional economies of the border

  17. Cost-Effectiveness Analysis of the Residential Provisions of the 2015 IECC for Georgia

    Energy Technology Data Exchange (ETDEWEB)

    Mendon, Vrushali V. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Zhao, Mingjie [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Taylor, Zachary T. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Poehlman, Eric A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2016-02-15

    The 2015 IECC provides cost-effective savings for residential buildings in Georgia. Moving to the 2015 IECC from the 2011 Georgia State Code base code is cost-effective for residential buildings in all climate zones in Georgia.

  18. A global interaction network maps a wiring diagram of cellular function

    Science.gov (United States)

    Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N.; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D.; Pelechano, Vicent; Styles, Erin B.; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S.; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F.; Li, Sheena C.; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; Luis, Bryan-Joseph San; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W.; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G.; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M.; Moore, Claire L.; Rosebrock, Adam P.; Caudy, Amy A.; Myers, Chad L.; Andrews, Brenda; Boone, Charles

    2017-01-01

    We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing over 23 million double mutants, identifying ~550,000 negative and ~350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. PMID:27708008

  19. Effect of interaction strength on robustness of controlling edge dynamics in complex networks

    Science.gov (United States)

    Pang, Shao-Peng; Hao, Fei

    2018-05-01

    Robustness plays a critical role in the controllability of complex networks to withstand failures and perturbations. Recent advances in the edge controllability show that the interaction strength among edges plays a more important role than network structure. Therefore, we focus on the effect of interaction strength on the robustness of edge controllability. Using three categories of all edges to quantify the robustness, we develop a universal framework to evaluate and analyze the robustness in complex networks with arbitrary structures and interaction strengths. Applying our framework to a large number of model and real-world networks, we find that the interaction strength is a dominant factor for the robustness in undirected networks. Meanwhile, the strongest robustness and the optimal edge controllability in undirected networks can be achieved simultaneously. Different from the case of undirected networks, the robustness in directed networks is determined jointly by the interaction strength and the network's degree distribution. Moreover, a stronger robustness is usually associated with a larger number of driver nodes required to maintain full control in directed networks. This prompts us to provide an optimization method by adjusting the interaction strength to optimize the robustness of edge controllability.

  20. Identification of human disease genes from interactome network using graphlet interaction.

    Directory of Open Access Journals (Sweden)

    Xiao-Dong Wang

    Full Text Available Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes.

  1. Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

    Science.gov (United States)

    Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

    2014-01-01

    Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

  2. An analysis pipeline for the inference of protein-protein interaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, Ronald C.; Singhal, Mudita; Daly, Don S.; Gilmore, Jason M.; Cannon, William R.; Domico, Kelly O.; White, Amanda M.; Auberry, Deanna L.; Auberry, Kenneth J.; Hooker, Brian S.; Hurst, G. B.; McDermott, Jason E.; McDonald, W. H.; Pelletier, Dale A.; Schmoyer, Denise A.; Wiley, H. S.

    2009-12-01

    An analysis pipeline has been created for deployment of a novel algorithm, the Bayesian Estimator of Protein-Protein Association Probabilities (BEPro), for use in the reconstruction of protein-protein interaction networks. We have combined the Software Environment for BIological Network Inference (SEBINI), an interactive environment for the deployment and testing of network inference algorithms that use high-throughput data, and the Collective Analysis of Biological Interaction Networks (CABIN), software that allows integration and analysis of protein-protein interaction and gene-to-gene regulatory evidence obtained from multiple sources, to allow interactions computed by BEPro to be stored, visualized, and further analyzed. Incorporating BEPro into SEBINI and automatically feeding the resulting inferred network into CABIN, we have created a structured workflow for protein-protein network inference and supplemental analysis from sets of mass spectrometry bait-prey experiment data. SEBINI demo site: https://www.emsl.pnl.gov /SEBINI/ Contact: ronald.taylor@pnl.gov. BEPro is available at http://www.pnl.gov/statistics/BEPro3/index.htm. Contact: ds.daly@pnl.gov. CABIN is available at http://www.sysbio.org/dataresources/cabin.stm. Contact: mudita.singhal@pnl.gov.

  3. Physical activity in Georgia state parks: A pilot study

    Science.gov (United States)

    Lincoln R. Larson; Jason W. Whiting; Gary T. Green

    2012-01-01

    This pilot study assessed the role of Georgia State Parks in the promotion of physical activity among different racial/ethnic and age groups. Data were collected at three state parks in north Georgia during the summer of 2009 using two research methods: behavior observations (N=2281) and intercept surveys (N=473).

  4. Interaction in agent-based economics: A survey on the network approach

    Science.gov (United States)

    Bargigli, Leonardo; Tedeschi, Gabriele

    2014-04-01

    In this paper we aim to introduce the reader to some basic concepts and instruments used in a wide range of economic networks models. In particular, we adopt the theory of random networks as the main tool to describe the relationship between the organization of interaction among individuals within different components of the economy and overall aggregate behavior. The focus is on the ways in which economic agents interact and the possible consequences of their interaction on the system. We show that network models are able to introduce complex phenomena in economic systems by allowing for the endogenous evolution of networks.

  5. The “Soft Power” policy of Turkey towards Georgia

    Directory of Open Access Journals (Sweden)

    Larisa Mgerovna Aleksanyan

    2016-01-01

    Full Text Available South Caucasus throughout history was at the epicenter of clashes of different religions, civilizations, nations and states. At present moment the interests of both regional (Turkey, Iran and global actors (the United States, NATO, the EU, Russia and others. intersect in the region. Global transformations, changing power relations in international relations have their direct influence on the political processes taking place in the region. These processes are also linked with the activities of Turkey, which aspire to regional leadership. It is Georgia, which serves as a corridor between Turkey and states of Central Asia and the South Caucasus. Turkey spreads its influence in Georgia in almost all areas using economic, military and political tools, as well as the Russian-Georgian deteriorated relations. To achieve its goals, Turkey is actively pursuing a strategy of "soft power", which further strengthens its influence in the country. Public diplomacy is a part of soft power, which also ensures the formation of a positive and attractive image of Turkey in Georgia. This article investigates the contemporary policy of "soft power" of Turkey towards Georgia. It analyses the basic tools, institutions and the direction of this policy, actively implemented by the Republic of Turkey. Particular attention is paid to the activities of the Gulen Movement in Georgia. The author makes general conclusions regarding the effectiveness of this policy.

  6. Georgia Institute of Technology chilled water system evaluation and master plan

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-05-15

    As the host of the Olympic Village for the 1996 Atlanta Olympics, Georgia Tech has experienced a surge in construction activities over the last three years. Over 1.3 million square feet of new buildings have been constructed on the Georgia Tech campus. This growth has placed a strain on the Georgia Tech community and challenged the facilities support staff charged with planning and organizing utility services. In concert with Olympic construction, utility planners have worked to ensure long term benefits for Georgia Tech facilities while meeting the short term requirements of the Olympic Games. The concentration of building construction in the northwest quadrant of the campus allowed planners to construct a satellite chilled water plant to serve the needs of this area and provide the opportunity to integrate this section of the campus with the main campus chilled water system. This assessment and master plan, funded in part by the US Department of Energy, has evaluated the chilled water infrastructure at Georgia Tech, identified ongoing problems and made recommendations for long term chilled water infrastructure development and efficiency improvements. The Georgia Tech office of Facilities and RDA Engineering, Inc. have worked together to assemble relevant information and prepare the recommendations contained in this document.

  7. Disentangling the co-structure of multilayer interaction networks: degree distribution and module composition in two-layer bipartite networks.

    Science.gov (United States)

    Astegiano, Julia; Altermatt, Florian; Massol, François

    2017-11-13

    Species establish different interactions (e.g. antagonistic, mutualistic) with multiple species, forming multilayer ecological networks. Disentangling network co-structure in multilayer networks is crucial to predict how biodiversity loss may affect the persistence of multispecies assemblages. Existing methods to analyse multilayer networks often fail to consider network co-structure. We present a new method to evaluate the modular co-structure of multilayer networks through the assessment of species degree co-distribution and network module composition. We focus on modular structure because of its high prevalence among ecological networks. We apply our method to two Lepidoptera-plant networks, one describing caterpillar-plant herbivory interactions and one representing adult Lepidoptera nectaring on flowers, thereby possibly pollinating them. More than 50% of the species established either herbivory or visitation interactions, but not both. These species were over-represented among plants and lepidopterans, and were present in most modules in both networks. Similarity in module composition between networks was high but not different from random expectations. Our method clearly delineates the importance of interpreting multilayer module composition similarity in the light of the constraints imposed by network structure to predict the potential indirect effects of species loss through interconnected modular networks.

  8. A Failed Experiment: Georgia's Tax Credit Scholarships for Private Schools. Special Summary

    Science.gov (United States)

    Southern Education Foundation, 2011

    2011-01-01

    Georgia is one of seven states that currently allow tax credits for scholarships to private schools. The law permits individual taxpayers in Georgia to reduce annual state taxes up to $2,500 for joint returns when they divert funds to a student scholarship organization (SSO). Georgia's law providing tax credits for private school tuition grants or…

  9. EVALUATING AUSTRALIAN FOOTBALL LEAGUE PLAYER CONTRIBUTIONS USING INTERACTIVE NETWORK SIMULATION

    Directory of Open Access Journals (Sweden)

    Jonathan Sargent

    2013-03-01

    Full Text Available This paper focuses on the contribution of Australian Football League (AFL players to their team's on-field network by simulating player interactions within a chosen team list and estimating the net effect on final score margin. A Visual Basic computer program was written, firstly, to isolate the effective interactions between players from a particular team in all 2011 season matches and, secondly, to generate a symmetric interaction matrix for each match. Negative binomial distributions were fitted to each player pairing in the Geelong Football Club for the 2011 season, enabling an interactive match simulation model given the 22 chosen players. Dynamic player ratings were calculated from the simulated network using eigenvector centrality, a method that recognises and rewards interactions with more prominent players in the team network. The centrality ratings were recorded after every network simulation and then applied in final score margin predictions so that each player's match contribution-and, hence, an optimal team-could be estimated. The paper ultimately demonstrates that the presence of highly rated players, such as Geelong's Jimmy Bartel, provides the most utility within a simulated team network. It is anticipated that these findings will facilitate optimal AFL team selection and player substitutions, which are key areas of interest to coaches. Network simulations are also attractive for use within betting markets, specifically to provide information on the likelihood of a chosen AFL team list "covering the line".

  10. Cytoscape: a software environment for integrated models of biomolecular interaction networks.

    Science.gov (United States)

    Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey

    2003-11-01

    Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

  11. 77 FR 34037 - Georgia-Alabama-South Carolina System of Projects

    Science.gov (United States)

    2012-06-08

    ... Marketing Division, Southeastern Power Administration, Department of Energy, 1166 Athens Tech Road, Elberton... a public information and comment forum for the Georgia-Alabama-South Carolina customers and... before June 5, 2012. The Georgia-Alabama-South Carolina customers, through their representatives, have...

  12. GETTING CLOSER TO EU STANDARDS - GEORGIA FISCAL GOVERNANCE ADJUSTMENT AND ITS IMPLICATIONS

    Directory of Open Access Journals (Sweden)

    David OBOLADZE

    2016-11-01

    Full Text Available This study focuses on fiscal governance from the perspective of developing the public finance management of Georgia. The paper investigates the fiscal governance framework in European Union countries and examines the impact of fiscal rules and budget procedures in EU countries. Well-designed fiscal frameworks are generally associated with better budgetary outcomes in terms of deficit and debt control. Following a thorough investigation of the current stance of fiscal governance in Georgia, the paper analyses the main medium and long term perspectives for Georgia to approximate with EU fiscal governance. The main objective of this paper is to provide policy guidelines needed for the appropriate and necessary reforms to ensure comprehensive, coherent and consistent fiscal governance framework for Georgia, which will improve the performance of public finance management and national economy of Georgia.

  13. Distribution of Georgia Oyster Reefs

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The feature class in this ESRI Geodatabase contains polygons representing oyster reefs along the Georgia coastal waterways from Chatham County south to Glynn County....

  14. Groundwater conditions and studies in Georgia, 2008-2009

    Science.gov (United States)

    Peck, Michael F.; Leeth, David C.; Painter, Jaime A.

    2011-01-01

    The U.S. Geological Survey collects groundwater data and conducts studies to monitor hydrologic conditions, better define groundwater resources, and address problems related to water supply, water use, and water quality. In Georgia, water levels were monitored continuously at 179 wells during 2008 and 181 wells during 2009. Because of missing data or short periods of record (less than 3 years) for several of these wells, a total of 161 wells are discussed in this report. These wells include 17 in the surficial aquifer system, 19 in the Brunswick aquifer and equivalent sediments, 66 in the Upper Floridan aquifer, 16 in the Lower Floridan aquifer and underlying units, 10 in the Claiborne aquifer, 1 in the Gordon aquifer, 11 in the Clayton aquifer, 12 in the Cretaceous aquifer system, 2 in Paleozoic-rock aquifers, and 7 in crystalline-rock aquifers. Data from the well network indicate that water levels generally rose during the 2008-2009 period, with water levels rising in 135 wells and declining in 26. In contrast, water levels declined over the period of record at 100 wells, increased at 56 wells, and remained relatively constant at 5 wells. In addition to continuous water-level data, periodic water-level measurements were collected and used to construct potentiometric-surface maps for the Upper Floridan aquifer in Camden, Charlton, and Ware Counties, Georgia, and adjacent counties in Florida during September 2008 and May 2009; in the Brunswick, Georgia area during July 2008 and July-August 2009; and in the City of Albany-Dougherty County, Georgia area during November 2008 and November 2009. In general, water levels in these areas were higher during 2009 than during 2008; however, the configuration of the potentiometric surfaces in each of the areas showed little change. Groundwater quality in the Floridan aquifer system is monitored in the Albany, Savannah, Brunswick, and Camden County areas of Georgia. In the Albany area, nitrate as nitrogen concentrations in the

  15. Georgia's Teacher Performance Assessment

    Science.gov (United States)

    Fenton, Anne Marie; Wetherington, Pamela

    2016-01-01

    Like most states, Georgia until recently depended on an assessment of content knowledge to award teaching licenses, along with a licensure recommendation from candidates' educator preparation programs. While the content assessment reflected candidates' grasp of subject matter, licensure decisions did not hinge on direct, statewide assessment of…

  16. Surface-Water Conditions in Georgia, Water Year 2005

    Science.gov (United States)

    Painter, Jaime A.; Landers, Mark N.

    2007-01-01

    INTRODUCTION The U.S. Geological Survey (USGS) Georgia Water Science Center-in cooperation with Federal, State, and local agencies-collected surface-water streamflow, water-quality, and ecological data during the 2005 Water Year (October 1, 2004-September 30, 2005). These data were compiled into layers of an interactive ArcReaderTM published map document (pmf). ArcReaderTM is a product of Environmental Systems Research Institute, Inc (ESRI?). Datasets represented on the interactive map are * continuous daily mean streamflow * continuous daily mean water levels * continuous daily total precipitation * continuous daily water quality (water temperature, specific conductance dissolved oxygen, pH, and turbidity) * noncontinuous peak streamflow * miscellaneous streamflow measurements * lake or reservoir elevation * periodic surface-water quality * periodic ecological data * historical continuous daily mean streamflow discontinued prior to the 2005 water year The map interface provides the ability to identify a station in spatial reference to the political boundaries of the State of Georgia and other features-such as major streams, major roads, and other collection stations. Each station is hyperlinked to a station summary showing seasonal and annual stream characteristics for the current year and for the period of record. For continuous discharge stations, the station summary includes a one page graphical summary page containing five graphs, a station map, and a photograph of the station. The graphs provide a quick overview of the current and period-of-record hydrologic conditions of the station by providing a daily mean discharge graph for the water year, monthly statistics graph for the water year and period of record, an annual mean streamflow graph for the period of record, an annual minimum 7-day average streamflow graph for the period of record, and an annual peak streamflow graph for the period of record. Additionally, data can be accessed through the layer's link

  17. Digital Ecology: Coexistence and Domination among Interacting Networks

    Science.gov (United States)

    Kleineberg, Kaj-Kolja; Boguñá, Marián

    2015-05-01

    The overwhelming success of Web 2.0, within which online social networks are key actors, has induced a paradigm shift in the nature of human interactions. The user-driven character of Web 2.0 services has allowed researchers to quantify large-scale social patterns for the first time. However, the mechanisms that determine the fate of networks at the system level are still poorly understood. For instance, the simultaneous existence of multiple digital services naturally raises questions concerning which conditions these services can coexist under. Analogously to the case of population dynamics, the digital world forms a complex ecosystem of interacting networks. The fitness of each network depends on its capacity to attract and maintain users’ attention, which constitutes a limited resource. In this paper, we introduce an ecological theory of the digital world which exhibits stable coexistence of several networks as well as the dominance of an individual one, in contrast to the competitive exclusion principle. Interestingly, our theory also predicts that the most probable outcome is the coexistence of a moderate number of services, in agreement with empirical observations.

  18. Water Use in Georgia by County for 2005; and Water-Use Trends, 1980-2005

    Science.gov (United States)

    Fanning, Julia L.; Trent, Victoria P.

    2009-01-01

    Water use for 2005 for each county in Georgia was estimated using data obtained from various Federal and State agencies and local sources. Total consumptive water use also was estimated for each county in Georgia for 2005. Water use is subdivided according to offstream and instream use. Offstream use is defined as water withdrawn or diverted from a ground- or surface-water source and transported to the place of use. Estimates for offstream water use include the categories of public supply, domestic, commercial, industrial, mining, irrigation, livestock, aquaculture, and thermoelectric power. Instream use is that which occurs within a stream channel for such purposes as hydroelectric-power generation, navigation, water-quality improvement, fish propagation, and recreation. The only category of instream use estimated was hydroelectric-power generation. Georgia law (the Georgia Ground-Water Use Act of 1972 and the Georgia Water Supply Act of 1978 [Georgia Department of Natural Resources, 2008a,b]) requires any water user who withdraws more than 100,000 gallons per day on a monthly average to obtain a withdrawal permit from the Georgia Environmental Protection Division. Permit holders generally must report their withdrawals by month. The Georgia Water-Use Program collects the reported information under the withdrawal permit system and the drinking-water permit system and stores the data in the Georgia Water-Use Data System.

  19. Ontology-based literature mining of E. coli vaccine-associated gene interaction networks.

    Science.gov (United States)

    Hur, Junguk; Özgür, Arzucan; He, Yongqun

    2017-03-14

    Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types. Using vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of

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

    Science.gov (United States)

    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.

  1. Some Remarks on Prediction of Drug-Target Interaction with Network Models.

    Science.gov (United States)

    Zhang, Shao-Wu; Yan, Xiao-Ying

    2017-01-01

    System-level understanding of the relationships between drugs and targets is very important for enhancing drug research, especially for drug function repositioning. The experimental methods used to determine drug-target interactions are usually time-consuming, tedious and expensive, and sometimes lack reproducibility. Thus, it is highly desired to develop computational methods for efficiently and effectively analyzing and detecting new drug-target interaction pairs. With the explosive growth of different types of omics data, such as genome, pharmacology, phenotypic, and other kinds of molecular networks, numerous computational approaches have been developed to predict Drug-Target Interactions (DTI). In this review, we make a survey on the recent advances in predicting drug-target interaction with network-based models from the following aspects: i) Available public data sources and benchmark datasets; ii) Drug/target similarity metrics; iii) Network construction; iv) Common network algorithms; v) Performance comparison of existing network-based DTI predictors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  2. Georgia State Briefing Book for low-level radioactive-waste management

    International Nuclear Information System (INIS)

    1981-08-01

    The Georgia State Briefing Book is one of a series of state briefing books on low-level radioactive waste management practices. It has been prepared to assist state and federal agency officials in planning for safe low-level radioactive waste disposal. The report contains a profile of low-level radioactive waste generators in Georgia. The profile is the result of a survey of NRC licensees in Georgia. The briefing book also contains a comprehensive assessment of low-level radioactive waste management issues and concerns as defined by all major interested parties including industry, government, the media, and interest groups. The assessment was developed through personal communications with representatives of interested parties, and through a review of media sources. Lastly, the briefing book provides demographic and socioeconomic data and a discussion of relevant government agencies and activities, all of which may impact waste management practices in Georgia

  3. Georgia State Briefing Book for low-level radioactive waste management

    International Nuclear Information System (INIS)

    1981-01-01

    The Georgia State Briefing Book is one of a series of state briefing books on low-level radioactive waste management practices. It has been prepared to assist state and federal agency officials in planning for safe low-level radioactive waste disposal. This report contains a profile of low-level radioactive waste generators in Georgia. The profile is the result of a survey of NRC licensees in Georgia. The briefing book also contains a comprehensive assessment of low-level radioactive waste management issues and concerns as defined by all major interested parties including industry, government, the media, and interest groups. The assessment was developed through personal communications with representatives of interested parties, and through a review of media sources. Lastly, the briefing book provides demographic and socioeconomic data and a discussion of relevant government agencies and activities, all of which may impact waste management practices in Georgia

  4. Limitation of degree information for analyzing the interaction evolution in online social networks

    Science.gov (United States)

    Shang, Ke-Ke; Yan, Wei-Sheng; Xu, Xiao-Ke

    2014-04-01

    Previously many studies on online social networks simply analyze the static topology in which the friend relationship once established, then the links and nodes will not disappear, but this kind of static topology may not accurately reflect temporal interactions on online social services. In this study, we define four types of users and interactions in the interaction (dynamic) network. We found that active, disappeared, new and super nodes (users) have obviously different strength distribution properties and this result also can be revealed by the degree characteristics of the unweighted interaction and friendship (static) networks. However, the active, disappeared, new and super links (interactions) only can be reflected by the strength distribution in the weighted interaction network. This result indicates the limitation of the static topology data on analyzing social network evolutions. In addition, our study uncovers the approximately stable statistics for the dynamic social network in which there are a large variation for users and interaction intensity. Our findings not only verify the correctness of our definitions, but also helped to study the customer churn and evaluate the commercial value of valuable customers in online social networks.

  5. 2009 Chatham County Georgia Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR generated point cloud acquired in spring 2009 for Chatham County, Georgia for the Metropolitan Planning Commission. The data are classified as follows: Class 1...

  6. Dynamic functional modules in co-expressed protein interaction networks of dilated cardiomyopathy

    Directory of Open Access Journals (Sweden)

    Oyang Yen-Jen

    2010-10-01

    Full Text Available Abstract Background Molecular networks represent the backbone of molecular activity within cells and provide opportunities for understanding the mechanism of diseases. While protein-protein interaction data constitute static network maps, integration of condition-specific co-expression information provides clues to the dynamic features of these networks. Dilated cardiomyopathy is a leading cause of heart failure. Although previous studies have identified putative biomarkers or therapeutic targets for heart failure, the underlying molecular mechanism of dilated cardiomyopathy remains unclear. Results We developed a network-based comparative analysis approach that integrates protein-protein interactions with gene expression profiles and biological function annotations to reveal dynamic functional modules under different biological states. We found that hub proteins in condition-specific co-expressed protein interaction networks tended to be differentially expressed between biological states. Applying this method to a cohort of heart failure patients, we identified two functional modules that significantly emerged from the interaction networks. The dynamics of these modules between normal and disease states further suggest a potential molecular model of dilated cardiomyopathy. Conclusions We propose a novel framework to analyze the interaction networks in different biological states. It successfully reveals network modules closely related to heart failure; more importantly, these network dynamics provide new insights into the cause of dilated cardiomyopathy. The revealed molecular modules might be used as potential drug targets and provide new directions for heart failure therapy.

  7. U.S. Strategic Interests and Georgias Prospects for NATO Membership

    Science.gov (United States)

    2015-03-01

    by the United States and the United Kingdom, as well as Georgia’s increasing efforts to either refurbish its existing hydroelectric power plants or...Bosnia and Herzegovina, Georgia, Macedonia, and Montenegro —all face serious challenges.”213 For Georgia, these challenges include its unresolved

  8. Designing Networked Adaptive Interactive Hybrid Systems

    NARCIS (Netherlands)

    Kester, L.J.H.M.

    2008-01-01

    Advances in network technologies enable distributed systems, operating in complex physical environments, to coordinate their activities over larger areas within shorter time intervals. In these systems humans and intelligent machines will, in close interaction, be able to reach their goals under

  9. Georgia's Economy in the Space of Contradictions Regional Powers

    Directory of Open Access Journals (Sweden)

    Andrew S. Degtev

    2016-01-01

    Full Text Available The article deals with the economic ties between Georgia and four countries neighbouring the Caucasus region: Russia, Turkey, Iran, and Kazakhstan. The authors focus their attention on regional analysis and, for comparison, give figures on Georgia's relations with three global players: the USA, the EU, and the PRC. The authors postulate at least three challenges to Russia’s interests in Georgia. First, both Georgian establishment and society regard integration with the EU and NATO as main goal of the state, which in case of NATO evidently contradicts Russian national interests. Second, from the economic point of view, the USA is no longer a financial driver of Georgian reforms. The EU, main trade partner of Georgia for the past 15 years, has replaced it. The CIS surpasses the EU in commodity turnover with Georgia, however it is in fact an amorphous organization that formally combines its member-states and lacks for common economic policy, unlike the European Union that acts as an integration association. Third, Chinese investment in Georgian infrastructure within the "New Silk Way" project serves as a ponderable alternative to Russian financial flow. For a comprehensive analysis of the situation the authors used some figures concerning commodity trade, FDI, cross-border financial flows, tourism, and transport development. Major pipeline branches, including the planned projects, are taken into account as well. The findings are based on the results of desk research, and on empirical data obtained through meetings with Georgian government officials.

  10. Characterizing interactions in online social networks during exceptional events

    Science.gov (United States)

    Omodei, Elisa; De Domenico, Manlio; Arenas, Alex

    2015-08-01

    Nowadays, millions of people interact on a daily basis on online social media like Facebook and Twitter, where they share and discuss information about a wide variety of topics. In this paper, we focus on a specific online social network, Twitter, and we analyze multiple datasets each one consisting of individuals' online activity before, during and after an exceptional event in terms of volume of the communications registered. We consider important events that occurred in different arenas that range from policy to culture or science. For each dataset, the users' online activities are modeled by a multilayer network in which each layer conveys a different kind of interaction, specifically: retweeting, mentioning and replying. This representation allows us to unveil that these distinct types of interaction produce networks with different statistical properties, in particular concerning the degree distribution and the clustering structure. These results suggests that models of online activity cannot discard the information carried by this multilayer representation of the system, and should account for the different processes generated by the different kinds of interactions. Secondly, our analysis unveils the presence of statistical regularities among the different events, suggesting that the non-trivial topological patterns that we observe may represent universal features of the social dynamics on online social networks during exceptional events.

  11. Current tobacco use and its associated factors among adults in Georgia: findings from Non-Communicable Disease Risk Factors STEPS Survey Georgia 2016

    Directory of Open Access Journals (Sweden)

    Nino Maglaklelidze

    2018-03-01

    Full Text Available Background Tobacco surveys of past decades show that tobacco use prevalence is high in Georgia; According to nationwide Noncommunicable Diseases (NCDC Risk Factors STEPS Survey 2010 30% of adult population are current tobacco users. Another Nationwide Tobacco Survey 2014 reported 28% of tobacco use prevalence among Georgian adults. However, there has been relatively little progress in systematic study of the factors associated with this high tobacco use. The current study aimed to assess the prevalence of tobacco use and its associated sociodemographic, behavioral and environmental factors in Georgia. Methods The current study in Georgia was a population-based STEPS survey of adults aged 18-69. A multi-stage cluster sample design was used to produce representative data for that age range in Georgia. The. A total of 5554 adults participated in the survey. The overall response rate was 75.7%. We assessed sociodemographics, behavioral and other health-related factors. Results The prevalence of current overall tobacco use was 31.1% (95 % CI: 29.0-33.1 which comprised of smoked tobacco use, smoked cigarettes and use of smokeless tobacco, 31.0% (95% 28.9-33.0 smoked tobacco, 29.9 (95% CI: 27.9-32.0 smoked cigarettes and 0.3 (95% CI: 0.0-0.6 use of smokeless tobacco. Smoking prevalence was significantly higher in men 57.1% (95% CI: 53.7-60.4 compared to women 7.1% (95% CI: 5.9-8.4, especially in younger age groups and with other substance abuse history (predominantly alcohol. Conclusions Despite of some efforts in the field of tobacco control, tobacco use (particularly smoking was high in Georgia. Males, younger age groups, and population with addictions to other substances (especially alcohol should be the primary target of behavioral interventions; The stricter implementation of tobacco control measures, including comprehensive ban of tobacco marketing and smoking in public places, improved health warnings on tobacco packages and anti

  12. Global Diffusion of Interactive Networks. The Impact of Culture

    OpenAIRE

    Maitland, Carleen

    1998-01-01

    The Internet and other interactive networks are diffusing across the globe at rates that vary from country to country. Typically, economic and market structure variables are used to explain these differences. The addition of culture to these variables will provide a more robust understanding of the differences in Internet and interactive network diffusion. Existing analyses that identify culture as a predictor of diffusion do not adequately specificy the dimensions of culture and their imp...

  13. Assessing tobacco marketing regulation implementation level in Georgia: evidence from Non Communicable Disease Risk Factors STEPS Survey Georgia 2016

    Directory of Open Access Journals (Sweden)

    Lela Sturua

    2018-03-01

    Full Text Available Background Tobacco use continues to be the leading cause of preventable deaths worldwide; the biggest burden of it falls on low- and middle-income countries and this trend is expected to widen further in case of inaction. The overall objective of the study is to describe and analyze the findings of the Noncommunicable Disease Risk Factors STEPS Survey Georgia 2016 related to tobacco marketing regulation. Methods The current study in Georgia was a population-based STEPS survey of randomly selected adults aged 18-69 within each sex and 10-year age-group. A multi-stage cluster sample design was used to produce representative data for that age range in Georgia. A total of 5554 adults participated in the current survey. We assessed level o tobacco marketing regulation implementation in Georgia. Results Study results reported high prevalence of tobacco use in Georgian population (31.1% (95 % CI: 29.0-33.1. Study findings showed that about half of the current smokers are exposed to anti-tobacco information on TV or radio 52.3% (95% CI: 48.9 - 55.7, whereas 35.5% (95% CI: 32.2 - 38.8 reported being exposed to cigarette marketing at points of sales of tobacco products and 4.7% (95% CI: 3.2-6.1 to any cigarette promotions. Health warnings on cigarette packs was reported to be noticed by 88.7% (95% CI: 85.8-91.6 of current smokers; only 33% (95% CI: 25.4 - 40.7 of them reported having thought about quitting because of these warnings. Conclusions The prevalence of smoking in Georgia is high compared to other countries of the European Region and it is very likely that smoking related NCDs burden will increase. Stricter tobacco control policies coupled with anti-tobacco media campaigns can address this problem. Improved health warnings on tobacco packages and total ban of tobacco advertisement, promotion and sponsorship should be implemented in order to overcome prevailed tobacco industry marketing strategies.

  14. Emergence of modularity and disassortativity in protein-protein interaction networks.

    Science.gov (United States)

    Wan, Xi; Cai, Shuiming; Zhou, Jin; Liu, Zengrong

    2010-12-01

    In this paper, we present a simple evolution model of protein-protein interaction networks by introducing a rule of small-preference duplication of a node, meaning that the probability of a node chosen to duplicate is inversely proportional to its degree, and subsequent divergence plus nonuniform heterodimerization based on some plausible mechanisms in biology. We show that our model cannot only reproduce scale-free connectivity and small-world pattern, but also exhibit hierarchical modularity and disassortativity. After comparing the features of our model with those of real protein-protein interaction networks, we believe that our model can provide relevant insights into the mechanism underlying the evolution of protein-protein interaction networks. © 2010 American Institute of Physics.

  15. 50 CFR Figure 4 to Part 223 - Georgia TED

    Science.gov (United States)

    2010-10-01

    ... 50 Wildlife and Fisheries 7 2010-10-01 2010-10-01 false Georgia TED 4 Figure 4 to Part 223 Wildlife and Fisheries NATIONAL MARINE FISHERIES SERVICE, NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE MARINE MAMMALS THREATENED MARINE AND ANADROMOUS SPECIES Pt. 223, Fig. 4 Figure 4 to Part 223—Georgia TED EC01JY91.048 [52 FR...

  16. Interactions between neural networks: a mechanism for tuning chaos and oscillations.

    Science.gov (United States)

    Wang, Lipo

    2007-06-01

    We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability.

  17. Network analysis applications in hydrology

    Science.gov (United States)

    Price, Katie

    2017-04-01

    Applied network theory has seen pronounced expansion in recent years, in fields such as epidemiology, computer science, and sociology. Concurrent development of analytical methods and frameworks has increased possibilities and tools available to researchers seeking to apply network theory to a variety of problems. While water and nutrient fluxes through stream systems clearly demonstrate a directional network structure, the hydrological applications of network theory remain under­explored. This presentation covers a review of network applications in hydrology, followed by an overview of promising network analytical tools that potentially offer new insights into conceptual modeling of hydrologic systems, identifying behavioral transition zones in stream networks and thresholds of dynamical system response. Network applications were tested along an urbanization gradient in Atlanta, Georgia, USA. Peachtree Creek and Proctor Creek. Peachtree Creek contains a nest of five long­term USGS streamflow and water quality gages, allowing network application of long­term flow statistics. The watershed spans a range of suburban and heavily urbanized conditions. Summary flow statistics and water quality metrics were analyzed using a suite of network analysis techniques, to test the conceptual modeling and predictive potential of the methodologies. Storm events and low flow dynamics during Summer 2016 were analyzed using multiple network approaches, with an emphasis on tomogravity methods. Results indicate that network theory approaches offer novel perspectives for understanding long­ term and event­based hydrological data. Key future directions for network applications include 1) optimizing data collection, 2) identifying "hotspots" of contaminant and overland flow influx to stream systems, 3) defining process domains, and 4) analyzing dynamic connectivity of various system components, including groundwater­surface water interactions.

  18. Residential Energy Efficiency Potential: Georgia

    Energy Technology Data Exchange (ETDEWEB)

    Wilson, Eric J [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-11-17

    Energy used by Georgia single-family homes that can be saved through cost-effective improvements. Prepared by Eric Wilson and Noel Merket, NREL, and Erin Boyd, U.S. Department of Energy Office of Energy Policy and Systems Analysis.

  19. Flower-Visiting Social Wasps and Plants Interaction: Network Pattern and Environmental Complexity

    Directory of Open Access Journals (Sweden)

    Mateus Aparecido Clemente

    2012-01-01

    Full Text Available Network analysis as a tool for ecological interactions studies has been widely used since last decade. However, there are few studies on the factors that shape network patterns in communities. In this sense, we compared the topological properties of the interaction network between flower-visiting social wasps and plants in two distinct phytophysiognomies in a Brazilian savanna (Riparian Forest and Rocky Grassland. Results showed that the landscapes differed in species richness and composition, and also the interaction networks between wasps and plants had different patterns. The network was more complex in the Riparian Forest, with a larger number of species and individuals and a greater amount of connections between them. The network specialization degree was more generalist in the Riparian Forest than in the Rocky Grassland. This result was corroborated by means of the nestedness index. In both networks was found asymmetry, with a large number of wasps per plant species. In general aspects, most wasps had low niche amplitude, visiting from one to three plant species. Our results suggest that differences in structural complexity of the environment directly influence the structure of the interaction network between flower-visiting social wasps and plants.

  20. Implementing the strengthened non-proliferation regime in Georgia

    International Nuclear Information System (INIS)

    Chelidze, L.

    2009-01-01

    A few years ago Georgia faced complicated problems in nuclear and radiation safety field, namely: weakness of infrastructure for state management, incomplete inventory of radiation sources, orphan sources all over the post soviet military bases and as a result several radiological emergencies, overexposed victims and high risk of attracting international terrorists to use the country as a rout for illegal movement of radiation sources or nuclear materials. IAEA policy and strategy for nonproliferation showed that it is not the one country problem. The coalition of democratic countries immediately responded to aroused problems. Step by step Georgia established a regulatory body, worked out national legislation, developed licensing and inspection activities, nearly finished installation of radiation portals at the whole perimeter of the country. Several successful cases of prevention of the illicit trafficking of nuclear materials through borders of Georgia identified country's ability to contribute its shear to the Global Nuclear security.(author)

  1. Georgia : Accounting and Auditing

    OpenAIRE

    World Bank

    2007-01-01

    This report provides an assessment of accounting, financial reporting and auditing requirements and practices within the enterprise and financial sectors in Georgia. The report uses International Financial Reporting Standards (IFRS), International Standards on Auditing (ISA) and draws on international experience and good practices in the field of accounting and audit regulation, including in ...

  2. Conference Report: 5th Annual Georgia Conference on Information Literacy

    Directory of Open Access Journals (Sweden)

    Rebecca Ziegler

    2009-11-01

    Full Text Available The 5th annual Georgia Conference on Information Literacy took place in Savannah, Georgia on October 3-4, 2008. Since its inception, this conference has drawn participants from across the United States and even a few from abroad. Jointly sponsored by the Zach S. Henderson Library, the Department of Writing and Linguistics, the College of Education, and the Center for Continuing Education at Georgia Southern University, the conference offers both theoretical and practical discussions of the complex issues involved in teaching students how to find, interpret and use information in emerging electronic technologies against the backdrop of one of America’s loveliest cities.

  3. A Global Protein Kinase and Phosphatase Interaction Network in Yeast

    Science.gov (United States)

    Breitkreutz, Ashton; Choi, Hyungwon; Sharom, Jeffrey R.; Boucher, Lorrie; Neduva, Victor; Larsen, Brett; Lin, Zhen-Yuan; Breitkreutz, Bobby-Joe; Stark, Chris; Liu, Guomin; Ahn, Jessica; Dewar-Darch, Danielle; Reguly, Teresa; Tang, Xiaojing; Almeida, Ricardo; Qin, Zhaohui Steve; Pawson, Tony; Gingras, Anne-Claude; Nesvizhskii, Alexey I.; Tyers, Mike

    2011-01-01

    The interactions of protein kinases and phosphatases with their regulatory subunits and substrates underpin cellular regulation. We identified a kinase and phosphatase interaction (KPI) network of 1844 interactions in budding yeast by mass spectrometric analysis of protein complexes. The KPI network contained many dense local regions of interactions that suggested new functions. Notably, the cell cycle phosphatase Cdc14 associated with multiple kinases that revealed roles for Cdc14 in mitogen-activated protein kinase signaling, the DNA damage response, and metabolism, whereas interactions of the target of rapamycin complex 1 (TORC1) uncovered new effector kinases in nitrogen and carbon metabolism. An extensive backbone of kinase-kinase interactions cross-connects the proteome and may serve to coordinate diverse cellular responses. PMID:20489023

  4. Identifying potential survival strategies of HIV-1 through virus-host protein interaction networks

    Directory of Open Access Journals (Sweden)

    Boucher Charles AB

    2010-07-01

    Full Text Available Abstract Background The National Institute of Allergy and Infectious Diseases has launched the HIV-1 Human Protein Interaction Database in an effort to catalogue all published interactions between HIV-1 and human proteins. In order to systematically investigate these interactions functionally and dynamically, we have constructed an HIV-1 human protein interaction network. This network was analyzed for important proteins and processes that are specific for the HIV life-cycle. In order to expose viral strategies, network motif analysis was carried out showing reoccurring patterns in virus-host dynamics. Results Our analyses show that human proteins interacting with HIV form a densely connected and central sub-network within the total human protein interaction network. The evaluation of this sub-network for connectivity and centrality resulted in a set of proteins essential for the HIV life-cycle. Remarkably, we were able to associate proteins involved in RNA polymerase II transcription with hubs and proteasome formation with bottlenecks. Inferred network motifs show significant over-representation of positive and negative feedback patterns between virus and host. Strikingly, such patterns have never been reported in combined virus-host systems. Conclusions HIV infection results in a reprioritization of cellular processes reflected by an increase in the relative importance of transcriptional machinery and proteasome formation. We conclude that during the evolution of HIV, some patterns of interaction have been selected for resulting in a system where virus proteins preferably interact with central human proteins for direct control and with proteasomal proteins for indirect control over the cellular processes. Finally, the patterns described by network motifs illustrate how virus and host interact with one another.

  5. Peptide microarrays to probe for competition for binding sites in a protein interaction network

    NARCIS (Netherlands)

    Sinzinger, M.D.S.; Ruttekolk, I.R.R.; Gloerich, J.; Wessels, H.; Chung, Y.D.; Adjobo-Hermans, M.J.W.; Brock, R.E.

    2013-01-01

    Cellular protein interaction networks are a result of the binding preferences of a particular protein and the entirety of interactors that mutually compete for binding sites. Therefore, the reconstruction of interaction networks by the accumulation of interaction networks for individual proteins

  6. NASCENT: an automatic protein interaction network generation tool for non-model organisms.

    Science.gov (United States)

    Banky, Daniel; Ordog, Rafael; Grolmusz, Vince

    2009-04-24

    Large quantity of reliable protein interaction data are available for model organisms in public depositories (e.g., MINT, DIP, HPRD, INTERACT). Most data correspond to experiments with the proteins of Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, Caenorhabditis elegans, Escherichia coli and Mus musculus. For other important organisms the data availability is poor or non-existent. Here we present NASCENT, a completely automatic web-based tool and also a downloadable Java program, capable of modeling and generating protein interaction networks even for non-model organisms. The tool performs protein interaction network modeling through gene-name mapping, and outputs the resulting network in graphical form and also in computer-readable graph-forms, directly applicable by popular network modeling software. http://nascent.pitgroup.org.

  7. Species co-occurrence networks: Can they reveal trophic and non-trophic interactions in ecological communities?

    Science.gov (United States)

    Freilich, Mara A; Wieters, Evie; Broitman, Bernardo R; Marquet, Pablo A; Navarrete, Sergio A

    2018-03-01

    Co-occurrence methods are increasingly utilized in ecology to infer networks of species interactions where detailed knowledge based on empirical studies is difficult to obtain. Their use is particularly common, but not restricted to, microbial networks constructed from metagenomic analyses. In this study, we test the efficacy of this procedure by comparing an inferred network constructed using spatially intensive co-occurrence data from the rocky intertidal zone in central Chile to a well-resolved, empirically based, species interaction network from the same region. We evaluated the overlap in the information provided by each network and the extent to which there is a bias for co-occurrence data to better detect known trophic or non-trophic, positive or negative interactions. We found a poor correspondence between the co-occurrence network and the known species interactions with overall sensitivity (probability of true link detection) equal to 0.469, and specificity (true non-interaction) equal to 0.527. The ability to detect interactions varied with interaction type. Positive non-trophic interactions such as commensalism and facilitation were detected at the highest rates. These results demonstrate that co-occurrence networks do not represent classical ecological networks in which interactions are defined by direct observations or experimental manipulations. Co-occurrence networks provide information about the joint spatial effects of environmental conditions, recruitment, and, to some extent, biotic interactions, and among the latter, they tend to better detect niche-expanding positive non-trophic interactions. Detection of links (sensitivity or specificity) was not higher for well-known intertidal keystone species than for the rest of consumers in the community. Thus, as observed in previous empirical and theoretical studies, patterns of interactions in co-occurrence networks must be interpreted with caution, especially when extending interaction

  8. Landslide Hazard in Georgia

    Science.gov (United States)

    Gaprindashvili, George; Tsereteli, Emil; Gaprindashvili, Merab

    2014-05-01

    In the last decades of the XX century, protect the population from geological hazards, to maintain land and safe operation of the engineering facilities has become the most important social - economic, demographic, political and environmental problems for the whole world. Georgia, with its scales of origination of the natural-catastrophic processes (landslide, mudflow, rockfall, erosion and etc.), their re-occurrence and with the negative results inflicted by these processes to the population, agricultural lands and engineering objects, is one of the most complex mountainous region. The extremely sensitive conditions were conditioned by: 1. Activation of highly intense earthquakes; 2. Activation of the negative meteorological events provoking the disaster processes on the background of global climatic changes and their abnormally frequent occurrence (mostly increased atmospheric precipitations, temperature and humidity); 3. Large-scale Human impact on the environment. Following the problem urgency, a number of departmental and research institutions have made their operations more intense in the given direction within the limits of their competence. First of all, the activity of the Department of Geology of Georgia (which is at present included in the National Environmental Agency of the Ministry of Environment and Natural Resources Protection), which mapped, identified and cataloged the hazardous processes on the territory of the country and identified the spatial limits and developmental regularities of these processes for tens of years. The increased risk of Geological catastrophes in Georgia first of all is caused by insufficient information between society and responsible persons toward this event. The existed situation needs the base assessment of natural disasters level, the identification of events, to determine their caused reasons, to develop special maps in GIS system, and continuous functioning of geo monitoring researches for develop safety early

  9. Responses to olfactory signals reflect network structure of flower-visitor interactions.

    Science.gov (United States)

    Junker, Robert R; Höcherl, Nicole; Blüthgen, Nico

    2010-07-01

    1. Network analyses provide insights into the diversity and complexity of ecological interactions and have motivated conclusions about community stability and co-evolution. However, biological traits and mechanisms such as chemical signals regulating the interactions between individual species--the microstructure of a network--are poorly understood. 2. We linked the responses of receivers (flower visitors) towards signals (flower scent) to the structure of a highly diverse natural flower-insect network. For each interaction, we define link temperature--a newly developed metric--as the deviation of the observed interaction strength from neutrality, assuming that animals randomly interact with flowers. 3. Link temperature was positively correlated to the specific visitors' responses to floral scents, experimentally examined in a mobile olfactometer. Thus, communication between plants and consumers via phytochemical signals reflects a significant part of the microstructure in a complex network. Negative as well as positive responses towards floral scents contributed to these results, where individual experience was important apart from innate behaviour. 4. Our results indicate that: (1) biological mechanisms have a profound impact on the microstructure of complex networks that underlies the outcome of aggregate statistics, and (2) floral scents act as a filter, promoting the visitation of some flower visitors, but also inhibiting the visitation of others.

  10. Using of solar energy in Republic of Georgia

    International Nuclear Information System (INIS)

    Meladze, N.

    1997-01-01

    The article presents the talk on the use of solar energy in Georgia given at the International Workshop on applied solar energy held in Tashkent(Uzbekistan) in June 1997. The main use of solar energy in the Republic is in solar heating systems developed and produced in Georgia. Presently 12 projects are in progress for effective use of renewable energy sources. Among them the research and development on photovoltaic cells on the basis of silicon and gallium arsenide solar cells. (A.A.D.)

  11. A global genetic interaction network maps a wiring diagram of cellular function.

    Science.gov (United States)

    Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D; Pelechano, Vicent; Styles, Erin B; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F; Li, Sheena C; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; San Luis, Bryan-Joseph; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M; Moore, Claire L; Rosebrock, Adam P; Caudy, Amy A; Myers, Chad L; Andrews, Brenda; Boone, Charles

    2016-09-23

    We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. Copyright © 2016, American Association for the Advancement of Science.

  12. Translocation of reindeer from South Georgia to the Falkland Islands

    Directory of Open Access Journals (Sweden)

    Cameron M. Bell

    2010-03-01

    Full Text Available This report describes the first translocation of reindeer Rangifer tarandus from South Georgia to the Falkland Islands, in the South Atlantic Ocean. Reindeer were introduced from Norway to the subantarctic island of South Georgia on three occasions in the early 1900s by Norwegian whalers, and today they exist as two discrete herds, numbering approximately 2600 individuals in total. Because of concerns over the impact on native vegetation, the long-term eradication of reindeer from South Georgia has recently been proposed. A translocation of reindeer to the Falkland Islands was undertaken in 2001 by the Falkland Island Government with two objectives: (1 to preserve the genetic resources of at least one of the South Georgia herds; and (2 to facilitate the diversification of the agricultural sector of the Falkland Islands by establishing a commercial reindeer herd. Techniques developed and used in North America for the successful relocation of large numbers of calves were adopted for the translocation. A total of 59 calves (26 females and 33 males were successfully translocated from South Georgia to the Falklands Islands in 2001, and subsequently produced their first offspring in 2003. Good husbandry practices and an understanding of biology and behaviour are essential for the successful translocation of reindeer.Flytting av rein fra Sør-Georgia til FalklandsøyeneAbstract in Norwegian / Sammendrag: Artikkelen beskriver den første overføring av rein Rangifer tarandus fra Sør-Georgia til Falklandsøyene i søratlanteren. Tamrein fra Norge ble flyttet til den subarktiske øya Sør-Georgia ved tre anledninger i perioden 1911 til 1925 i forbindelse med den norske hvalfangsten der. I dag består bestanden av rundt regnet 2600 dyr fordelt på to geografisk atskilte flokker. Av hensyn til den naturlige vegetasjonen på øya er det forslag om å på sikt utrydde reinbestanden på øya. Regjeringen på Falklandsøyene foretok en første overføring av

  13. Cytoprophet: a Cytoscape plug-in for protein and domain interaction networks inference.

    Science.gov (United States)

    Morcos, Faruck; Lamanna, Charles; Sikora, Marcin; Izaguirre, Jesús

    2008-10-01

    Cytoprophet is a software tool that allows prediction and visualization of protein and domain interaction networks. It is implemented as a plug-in of Cytoscape, an open source software framework for analysis and visualization of molecular networks. Cytoprophet implements three algorithms that predict new potential physical interactions using the domain composition of proteins and experimental assays. The algorithms for protein and domain interaction inference include maximum likelihood estimation (MLE) using expectation maximization (EM); the set cover approach maximum specificity set cover (MSSC) and the sum-product algorithm (SPA). After accepting an input set of proteins with Uniprot ID/Accession numbers and a selected prediction algorithm, Cytoprophet draws a network of potential interactions with probability scores and GO distances as edge attributes. A network of domain interactions between the domains of the initial protein list can also be generated. Cytoprophet was designed to take advantage of the visual capabilities of Cytoscape and be simple to use. An example of inference in a signaling network of myxobacterium Myxococcus xanthus is presented and available at Cytoprophet's website. http://cytoprophet.cse.nd.edu.

  14. QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks.

    Directory of Open Access Journals (Sweden)

    Asa Thibodeau

    2016-06-01

    Full Text Available Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1 building and visualizing chromatin interaction networks, 2 annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3 querying network components based on gene name or chromosome location, and 4 utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions.QuIN's web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/.

  15. QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks.

    Science.gov (United States)

    Thibodeau, Asa; Márquez, Eladio J; Luo, Oscar; Ruan, Yijun; Menghi, Francesca; Shin, Dong-Guk; Stitzel, Michael L; Vera-Licona, Paola; Ucar, Duygu

    2016-06-01

    Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions. QuIN's web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/.

  16. Data management of protein interaction networks

    CERN Document Server

    Cannataro, Mario

    2012-01-01

    Interactomics: a complete survey from data generation to knowledge extraction With the increasing use of high-throughput experimental assays, more and more protein interaction databases are becoming available. As a result, computational analysis of protein-to-protein interaction (PPI) data and networks, now known as interactomics, has become an essential tool to determine functionally associated proteins. From wet lab technologies to data management to knowledge extraction, this timely book guides readers through the new science of interactomics, giving them the tools needed to: Generate

  17. Topology and weights in a protein domain interaction network--a novel way to predict protein interactions.

    Science.gov (United States)

    Wuchty, Stefan

    2006-05-23

    While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. We consider a web of interactions between protein domains of the Protein Family database (PFAM), which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we show a simple way to predict potential protein interactions

  18. Unified Alignment of Protein-Protein Interaction Networks.

    Science.gov (United States)

    Malod-Dognin, Noël; Ban, Kristina; Pržulj, Nataša

    2017-04-19

    Paralleling the increasing availability of protein-protein interaction (PPI) network data, several network alignment methods have been proposed. Network alignments have been used to uncover functionally conserved network parts and to transfer annotations. However, due to the computational intractability of the network alignment problem, aligners are heuristics providing divergent solutions and no consensus exists on a gold standard, or which scoring scheme should be used to evaluate them. We comprehensively evaluate the alignment scoring schemes and global network aligners on large scale PPI data and observe that three methods, HUBALIGN, L-GRAAL and NATALIE, regularly produce the most topologically and biologically coherent alignments. We study the collective behaviour of network aligners and observe that PPI networks are almost entirely aligned with a handful of aligners that we unify into a new tool, Ulign. Ulign enables complete alignment of two networks, which traditional global and local aligners fail to do. Also, multiple mappings of Ulign define biologically relevant soft clusterings of proteins in PPI networks, which may be used for refining the transfer of annotations across networks. Hence, PPI networks are already well investigated by current aligners, so to gain additional biological insights, a paradigm shift is needed. We propose such a shift come from aligning all available data types collectively rather than any particular data type in isolation from others.

  19. Detection of protein complex from protein-protein interaction network using Markov clustering

    International Nuclear Information System (INIS)

    Ochieng, P J; Kusuma, W A; Haryanto, T

    2017-01-01

    Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks. (paper)

  20. User-Centric Secure Cross-Site Interaction Framework for Online Social Networking Services

    Science.gov (United States)

    Ko, Moo Nam

    2011-01-01

    Social networking service is one of major technological phenomena on Web 2.0. Hundreds of millions of users are posting message, photos, and videos on their profiles and interacting with other users, but the sharing and interaction are limited within the same social networking site. Although users can share some content on a social networking site…

  1. Topological and functional properties of the small GTPases protein interaction network.

    Directory of Open Access Journals (Sweden)

    Anna Delprato

    Full Text Available Small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran regulate key cellular processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. A great deal of experimental evidence supports the existence of signaling cascades and feedback loops within and among the small GTPase subfamilies suggesting that these proteins function in a coordinated and cooperative manner. The interplay occurs largely through association with bi-partite regulatory and effector proteins but can also occur through the active form of the small GTPases themselves. In order to understand the connectivity of the small GTPases signaling routes, a systems-level approach that analyzes data describing direct and indirect interactions was used to construct the small GTPases protein interaction network. The data were curated from the Search Tool for the Retrieval of Interacting Genes (STRING database and include only experimentally validated interactions. The network method enables the conceptualization of the overall structure as well as the underlying organization of the protein-protein interactions. The interaction network described here is comprised of 778 nodes and 1943 edges and has a scale-free topology. Rac1, Cdc42, RhoA, and HRas are identified as the hubs. Ten sub-network motifs are also identified in this study with themes in apoptosis, cell growth/proliferation, vesicle traffic, cell adhesion/junction dynamics, the nicotinamide adenine dinucleotide phosphate (NADPH oxidase response, transcription regulation, receptor-mediated endocytosis, gene silencing, and growth factor signaling. Bottleneck proteins that bridge signaling paths and proteins that overlap in multiple small GTPase networks are described along with the functional annotation of all proteins in the network.

  2. Network of microRNAs-mRNAs Interactions in Pancreatic Cancer

    Science.gov (United States)

    Naderi, Elnaz; Mostafaei, Mehdi; Pourshams, Akram

    2014-01-01

    Background. MicroRNAs are small RNA molecules that regulate the expression of certain genes through interaction with mRNA targets and are mainly involved in human cancer. This study was conducted to make the network of miRNAs-mRNAs interactions in pancreatic cancer as the fourth leading cause of cancer death. Methods. 56 miRNAs that were exclusively expressed and 1176 genes that were downregulated or silenced in pancreas cancer were extracted from beforehand investigations. MiRNA–mRNA interactions data analysis and related networks were explored using MAGIA tool and Cytoscape 3 software. Functional annotations of candidate genes in pancreatic cancer were identified by DAVID annotation tool. Results. This network is made of 217 nodes for mRNA, 15 nodes for miRNA, and 241 edges that show 241 regulations between 15 miRNAs and 217 target genes. The miR-24 was the most significantly powerful miRNA that regulated series of important genes. ACVR2B, GFRA1, and MTHFR were significant target genes were that downregulated. Conclusion. Although the collected previous data seems to be a treasure trove, there was no study simultaneous to analysis of miRNAs and mRNAs interaction. Network of miRNA-mRNA interactions will help to corroborate experimental remarks and could be used to refine miRNA target predictions for developing new therapeutic approaches. PMID:24895587

  3. Network of microRNAs-mRNAs Interactions in Pancreatic Cancer

    Directory of Open Access Journals (Sweden)

    Elnaz Naderi

    2014-01-01

    Full Text Available Background. MicroRNAs are small RNA molecules that regulate the expression of certain genes through interaction with mRNA targets and are mainly involved in human cancer. This study was conducted to make the network of miRNAs-mRNAs interactions in pancreatic cancer as the fourth leading cause of cancer death. Methods. 56 miRNAs that were exclusively expressed and 1176 genes that were downregulated or silenced in pancreas cancer were extracted from beforehand investigations. MiRNA–mRNA interactions data analysis and related networks were explored using MAGIA tool and Cytoscape 3 software. Functional annotations of candidate genes in pancreatic cancer were identified by DAVID annotation tool. Results. This network is made of 217 nodes for mRNA, 15 nodes for miRNA, and 241 edges that show 241 regulations between 15 miRNAs and 217 target genes. The miR-24 was the most significantly powerful miRNA that regulated series of important genes. ACVR2B, GFRA1, and MTHFR were significant target genes were that downregulated. Conclusion. Although the collected previous data seems to be a treasure trove, there was no study simultaneous to analysis of miRNAs and mRNAs interaction. Network of miRNA-mRNA interactions will help to corroborate experimental remarks and could be used to refine miRNA target predictions for developing new therapeutic approaches.

  4. Evaluation of the ground-water resources of coastal Georgia: preliminary report of the data available as of July 1983

    Science.gov (United States)

    Krause, Richard E.

    1984-01-01

    A compilation of ground-water data that have been collected for nearly 100 years in the coastal area of Georgia is presented in this report. The compilation of pertinent data indicates what information is available for use in the evaluation of the ground-water resources of the 13 counties of coastal Georgia. Also included in this report is a fairly complete discussion of previous and ongoing investigations and monitoring networks, and an extensive list of references. Maps at 1:24,000 and 1:1,000,000 scales contain well locations and identifiers for all wells in the Ground Water Site Inventory (GWSI) data base of the National Water Data Storage and retrieval System (WATSTORE). Tabular summaries of selected site information from GWSI, including well identifiers and names, latitude-longitude location, depth of well, altitude of land surface, and use of water are presented. Water-use data from the National Water Use Data System, and water use for irrigation from the University of Georgia, Department of Agriculture survey, also are tabulated. Also included are pertinent information on geophysical surveys and data obtained, and proposed project activities, particularly test-monitor well drilling. The data in this report were collected and compiled as part of the cooperative activities between the U.S. Geological Survey and other agencies.

  5. Evaluation of the ground-water resources of coastal Georgia; preliminary report on the data available as of July 1983

    Science.gov (United States)

    Krause, Richard E.; Matthews, Sharon E.; Gill, Harold E.

    1984-01-01

    A compilation of ground-water data that have been collected for nearly 100 years in the coastal area of Georgia as part of cooperative activities between the U.S. Geological Survey and other agencies is presented in this report. The compilation of pertinent data indicates that information is available for use in the evaluation of the ground-water resources of the 13 counties of coastal Georgia. Included in this report is a fairly complete discussion of previous and ongoing investigations and monitoring networks, and an extensive list of references. Maps at 1:24,000, 1:100,000; and 1:1000,000 scales contain well locations and identifers for all wells in the Ground Water Site Inventory (GWSI) data base of the National Water Data Storage and Retrieval System (WATSTORE). Tabular summaries of selected site information from GWSI, including well identifiers and names , latitude-longitude location, depth of well, altitude of land surface, and use of water are presented. Water-use data from the National Water Use Data System, and water use for irrigation from the University of Georgia, Department of Agriculture survey , are tabulated. Also included are pertinent information on geophysical surveys and data obtained, and proposed project activities, particularly test-monitor well drilling.

  6. Communicating Georgia : Georgia's information campaign in the 2008 war with Russia

    OpenAIRE

    Jugaste, Artur

    2011-01-01

    During the 2008 South Ossetia war, Georgia and Russia fought what the English-language media called "a public relations war“. This was an interesting example of modern information warfare where governments allied with public relations agencies battled for symbolic power on the media field. This study investigates the information campaign that the Georgian government launched to promote their framing of the conflict in the English-language media. First-hand information about the campaign strat...

  7. Synergistic interactions promote behavior spreading and alter phase transitions on multiplex networks

    Science.gov (United States)

    Liu, Quan-Hui; Wang, Wei; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

    2018-02-01

    Synergistic interactions are ubiquitous in the real world. Recent studies have revealed that, for a single-layer network, synergy can enhance spreading and even induce an explosive contagion. There is at the present a growing interest in behavior spreading dynamics on multiplex networks. What is the role of synergistic interactions in behavior spreading in such networked systems? To address this question, we articulate a synergistic behavior spreading model on a double layer network, where the key manifestation of the synergistic interactions is that the adoption of one behavior by a node in one layer enhances its probability of adopting the behavior in the other layer. A general result is that synergistic interactions can greatly enhance the spreading of the behaviors in both layers. A remarkable phenomenon is that the interactions can alter the nature of the phase transition associated with behavior adoption or spreading dynamics. In particular, depending on the transmission rate of one behavior in a network layer, synergistic interactions can lead to a discontinuous (first-order) or a continuous (second-order) transition in the adoption scope of the other behavior with respect to its transmission rate. A surprising two-stage spreading process can arise: due to synergy, nodes having adopted one behavior in one layer adopt the other behavior in the other layer and then prompt the remaining nodes in this layer to quickly adopt the behavior. Analytically, we develop an edge-based compartmental theory and perform a bifurcation analysis to fully understand, in the weak synergistic interaction regime where the dynamical correlation between the network layers is negligible, the role of the interactions in promoting the social behavioral spreading dynamics in the whole system.

  8. Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.

    Science.gov (United States)

    Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

    2017-01-01

    The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.

  9. Structural Modeling and Characteristics Analysis of Flow Interaction Networks in the Internet

    International Nuclear Information System (INIS)

    Wu Xiao-Yu; Gu Ren-Tao; Pan Zhuo-Ya; Jin Wei-Qi; Ji Yue-Feng

    2015-01-01

    Applying network duality and elastic mechanics, we investigate the interactions among Internet flows by constructing a weighted undirected network, where the vertices and the edges represent the flows and the mutual dependence between flows, respectively. Based on the obtained flow interaction network, we find the existence of ‘super flow’ in the Internet, indicating that some flows have a great impact on a huge number of other flows; moreover, one flow can spread its influence to another through a limited quantity of flows (less than 5 in the experimental simulations), which shows strong small-world characteristics like the social network. To reflect the flow interactions in the physical network congestion evaluation, the ‘congestion coefficient’ is proposed as a new metric which shows a finer observation on congestion than the conventional one. (paper)

  10. Dynamic and interacting complex networks

    Science.gov (United States)

    Dickison, Mark E.

    This thesis employs methods of statistical mechanics and numerical simulations to study some aspects of dynamic and interacting complex networks. The mapping of various social and physical phenomena to complex networks has been a rich field in the past few decades. Subjects as broad as petroleum engineering, scientific collaborations, and the structure of the internet have all been analyzed in a network physics context, with useful and universal results. In the first chapter we introduce basic concepts in networks, including the two types of network configurations that are studied and the statistical physics and epidemiological models that form the framework of the network research, as well as covering various previously-derived results in network theory that are used in the work in the following chapters. In the second chapter we introduce a model for dynamic networks, where the links or the strengths of the links change over time. We solve the model by mapping dynamic networks to the problem of directed percolation, where the direction corresponds to the time evolution of the network. We show that the dynamic network undergoes a percolation phase transition at a critical concentration pc, that decreases with the rate r at which the network links are changed. The behavior near criticality is universal and independent of r. We find that for dynamic random networks fundamental laws are changed: i) The size of the giant component at criticality scales with the network size N for all values of r, rather than as N2/3 in static network, ii) In the presence of a broad distribution of disorder, the optimal path length between two nodes in a dynamic network scales as N1/2, compared to N1/3 in a static network. The third chapter consists of a study of the effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered model in the presence of quarantine, where susceptible

  11. Perspectives of Nurses Pursuing Doctoral Degrees in Georgia: Implications for Recruitment.

    Science.gov (United States)

    Wheeler, Rebecca McCombs; Eichelberger, Lisa Wright

    2017-08-01

    Increasing the number of nurses with doctorates is a goal of the nursing profession. The Georgia Nursing Leadership Coalition developed a survey to understand the perspectives of nurses pursuing doctoral degrees in Georgia to improve recruitment and retention strategies. A 26-item online survey was distributed to all students enrolled in Georgia-based doctoral programs in nursing in spring 2014. One hundred fifty responses were received (54% response rate). Most students first seriously considered doctoral education during their master's programs or more than 5 years into practice. For most, obtaining a doctoral degree was a personal life goal. Work-life balance was the most significant barrier. Recruitment of nurses to doctoral programs should focus on messaging, timing, and highlighting the unique aspects of programs. Schools should work to reduce barriers. Understanding students' perspectives of doctoral education in nursing can improve recruitment strategies and increase the number of nurses graduating with doctorates in Georgia. [J Nurs Educ. 2017;56(8):466-470.]. Copyright 2017, SLACK Incorporated.

  12. Fluctuating interaction network and time-varying stability of a natural fish community

    Science.gov (United States)

    Ushio, Masayuki; Hsieh, Chih-Hao; Masuda, Reiji; Deyle, Ethan R.; Ye, Hao; Chang, Chun-Wei; Sugihara, George; Kondoh, Michio

    2018-02-01

    Ecological theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current ecological theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of ecological communities in nature.

  13. Effect of dataset selection on the topological interpretation of protein interaction networks

    Directory of Open Access Journals (Sweden)

    Robertson David L

    2005-09-01

    Full Text Available Abstract Background Studies of the yeast protein interaction network have revealed distinct correlations between the connectivity of individual proteins within the network and the average connectivity of their neighbours. Although a number of biological mechanisms have been proposed to account for these findings, the significance and influence of the specific datasets included in these studies has not been appreciated adequately. Results We show how the use of different interaction data sets, such as those resulting from high-throughput or small-scale studies, and different modelling methodologies for the derivation pair-wise protein interactions, can dramatically change the topology of these networks. Furthermore, we show that some of the previously reported features identified in these networks may simply be the result of experimental or methodological errors and biases. Conclusion When performing network-based studies, it is essential to define what is meant by the term "interaction" and this must be taken into account when interpreting the topologies of the networks generated. Consideration must be given to the type of data included and appropriate controls that take into account the idiosyncrasies of the data must be selected

  14. Integration and visualization of non-coding RNA and protein interaction networks

    OpenAIRE

    Junge, Alexander; Refsgaard, Jan Christian; Garde, Christian; Pan, Xiaoyong; Santos Delgado, Alberto; Anthon, Christian; Alkan, Ferhat; von Mering, Christian; Workman, Christopher; Jensen, Lars Juhl; Gorodkin, Jan

    2015-01-01

    Non-coding RNAs (ncRNAs) fulfill a diverse set of biological functions relying on interactions with other molecular entities. The advent of new experimental and computational approaches makes it possible to study ncRNAs and their associations on an unprecedented scale. We present RAIN (RNA Association and Interaction Networks) - a database that combines ncRNA-ncRNA, ncRNA-mRNA and ncRNA-protein interactions with large-scale protein association networks available in the STRING database. By int...

  15. Major component analysis of dynamic networks of physiologic organ interactions

    International Nuclear Information System (INIS)

    Liu, Kang K L; Ma, Qianli D Y; Ivanov, Plamen Ch; Bartsch, Ronny P

    2015-01-01

    The human organism is a complex network of interconnected organ systems, where the behavior of one system affects the dynamics of other systems. Identifying and quantifying dynamical networks of diverse physiologic systems under varied conditions is a challenge due to the complexity in the output dynamics of the individual systems and the transient and nonlinear characteristics of their coupling. We introduce a novel computational method based on the concept of time delay stability and major component analysis to investigate how organ systems interact as a network to coordinate their functions. We analyze a large database of continuously recorded multi-channel physiologic signals from healthy young subjects during night-time sleep. We identify a network of dynamic interactions between key physiologic systems in the human organism. Further, we find that each physiologic state is characterized by a distinct network structure with different relative contribution from individual organ systems to the global network dynamics. Specifically, we observe a gradual decrease in the strength of coupling of heart and respiration to the rest of the network with transition from wake to deep sleep, and in contrast, an increased relative contribution to network dynamics from chin and leg muscle tone and eye movement, demonstrating a robust association between network topology and physiologic function. (paper)

  16. Novel recurrent neural network for modelling biological networks: oscillatory p53 interaction dynamics.

    Science.gov (United States)

    Ling, Hong; Samarasinghe, Sandhya; Kulasiri, Don

    2013-12-01

    Understanding the control of cellular networks consisting of gene and protein interactions and their emergent properties is a central activity of Systems Biology research. For this, continuous, discrete, hybrid, and stochastic methods have been proposed. Currently, the most common approach to modelling accurate temporal dynamics of networks is ordinary differential equations (ODE). However, critical limitations of ODE models are difficulty in kinetic parameter estimation and numerical solution of a large number of equations, making them more suited to smaller systems. In this article, we introduce a novel recurrent artificial neural network (RNN) that addresses above limitations and produces a continuous model that easily estimates parameters from data, can handle a large number of molecular interactions and quantifies temporal dynamics and emergent systems properties. This RNN is based on a system of ODEs representing molecular interactions in a signalling network. Each neuron represents concentration change of one molecule represented by an ODE. Weights of the RNN correspond to kinetic parameters in the system and can be adjusted incrementally during network training. The method is applied to the p53-Mdm2 oscillation system - a crucial component of the DNA damage response pathways activated by a damage signal. Simulation results indicate that the proposed RNN can successfully represent the behaviour of the p53-Mdm2 oscillation system and solve the parameter estimation problem with high accuracy. Furthermore, we presented a modified form of the RNN that estimates parameters and captures systems dynamics from sparse data collected over relatively large time steps. We also investigate the robustness of the p53-Mdm2 system using the trained RNN under various levels of parameter perturbation to gain a greater understanding of the control of the p53-Mdm2 system. Its outcomes on robustness are consistent with the current biological knowledge of this system. As more

  17. Unravelling Darwin's entangled bank: architecture and robustness of mutualistic networks with multiple interaction types.

    Science.gov (United States)

    Dáttilo, Wesley; Lara-Rodríguez, Nubia; Jordano, Pedro; Guimarães, Paulo R; Thompson, John N; Marquis, Robert J; Medeiros, Lucas P; Ortiz-Pulido, Raul; Marcos-García, Maria A; Rico-Gray, Victor

    2016-11-30

    Trying to unravel Darwin's entangled bank further, we describe the architecture of a network involving multiple forms of mutualism (pollination by animals, seed dispersal by birds and plant protection by ants) and evaluate whether this multi-network shows evidence of a structure that promotes robustness. We found that species differed strongly in their contributions to the organization of the multi-interaction network, and that only a few species contributed to the structuring of these patterns. Moreover, we observed that the multi-interaction networks did not enhance community robustness compared with each of the three independent mutualistic networks when analysed across a range of simulated scenarios of species extinction. By simulating the removal of highly interacting species, we observed that, overall, these species enhance network nestedness and robustness, but decrease modularity. We discuss how the organization of interlinked mutualistic networks may be essential for the maintenance of ecological communities, and therefore the long-term ecological and evolutionary dynamics of interactive, species-rich communities. We suggest that conserving these keystone mutualists and their interactions is crucial to the persistence of species-rich mutualistic assemblages, mainly because they support other species and shape the network organization. © 2016 The Author(s).

  18. 2013 Athens-Clarke County, Georgia Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of 0.5 foot pixel resolution, four band (RGB, Near IR) orthoimages covering Athens-Clarke Georgia. An orthoimage is remotely sensed image data...

  19. Modeling interacting dynamic networks: II. Systematic study of the statistical properties of cross-links between two networks with preferred degrees

    International Nuclear Information System (INIS)

    Liu, Wenjia; Schmittmann, B; Zia, R K P

    2014-01-01

    In a recent work (Liu et al, 2013 J. Stat. Mech. P08001), we introduced dynamic networks with preferred degrees and presented simulation and analytic studies of a single, homogeneous system as well as two interacting networks. Here, we extend these studies to a wider range of parameter space, in a more systematic fashion. Though the interaction we introduced seems simple and intuitive, it produced dramatically different behavior in the single- and two-network systems. Specifically, partitioning the single network into two identical sectors, we find the cross-link distribution to be a sharply peaked Gaussian. In stark contrast, we find a very broad and flat plateau in the case of two interacting identical networks. A sound understanding of this phenomenon remains elusive. Exploring more asymmetric interacting networks, we discover a kind of ‘universal behavior’ for systems in which the ‘introverts’ (nodes with smaller preferred degree) are far outnumbered. Remarkably, an approximation scheme for their degree distribution can be formulated, leading to very successful predictions. (paper)

  20. Linking plant specialization to dependence in interactions for seed set in pollination networks.

    Science.gov (United States)

    Tur, Cristina; Castro-Urgal, Rocío; Traveset, Anna

    2013-01-01

    Studies on pollination networks have provided valuable information on the number, frequency, distribution and identity of interactions between plants and pollinators. However, little is still known on the functional effect of these interactions on plant reproductive success. Information on the extent to which plants depend on such interactions will help to make more realistic predictions of the potential impacts of disturbances on plant-pollinator networks. Plant functional dependence on pollinators (all interactions pooled) can be estimated by comparing seed set with and without pollinators (i.e. bagging flowers to exclude them). Our main goal in this study was thus to determine whether plant dependence on current insect interactions is related to plant specialization in a pollination network. We studied two networks from different communities, one in a coastal dune and one in a mountain. For ca. 30% of plant species in each community, we obtained the following specialization measures: (i) linkage level (number of interactions), (ii) diversity of interactions, and (iii) closeness centrality (a measure of how much a species is connected to other plants via shared pollinators). Phylogenetically controlled regression analyses revealed that, for the largest and most diverse coastal community, plants highly dependent on pollinators were the most generalists showing the highest number and diversity of interactions as well as occupying central positions in the network. The mountain community, by contrast, did not show such functional relationship, what might be attributable to their lower flower-resource heterogeneity and diversity of interactions. We conclude that plants with a wide array of pollinator interactions tend to be those that are more strongly dependent upon them for seed production and thus might be those more functionally vulnerable to the loss of network interaction, although these outcomes might be context-dependent.

  1. Linking plant specialization to dependence in interactions for seed set in pollination networks.

    Directory of Open Access Journals (Sweden)

    Cristina Tur

    Full Text Available Studies on pollination networks have provided valuable information on the number, frequency, distribution and identity of interactions between plants and pollinators. However, little is still known on the functional effect of these interactions on plant reproductive success. Information on the extent to which plants depend on such interactions will help to make more realistic predictions of the potential impacts of disturbances on plant-pollinator networks. Plant functional dependence on pollinators (all interactions pooled can be estimated by comparing seed set with and without pollinators (i.e. bagging flowers to exclude them. Our main goal in this study was thus to determine whether plant dependence on current insect interactions is related to plant specialization in a pollination network. We studied two networks from different communities, one in a coastal dune and one in a mountain. For ca. 30% of plant species in each community, we obtained the following specialization measures: (i linkage level (number of interactions, (ii diversity of interactions, and (iii closeness centrality (a measure of how much a species is connected to other plants via shared pollinators. Phylogenetically controlled regression analyses revealed that, for the largest and most diverse coastal community, plants highly dependent on pollinators were the most generalists showing the highest number and diversity of interactions as well as occupying central positions in the network. The mountain community, by contrast, did not show such functional relationship, what might be attributable to their lower flower-resource heterogeneity and diversity of interactions. We conclude that plants with a wide array of pollinator interactions tend to be those that are more strongly dependent upon them for seed production and thus might be those more functionally vulnerable to the loss of network interaction, although these outcomes might be context-dependent.

  2. Epidemic spreading in networks with nonrandom long-range interactions.

    Science.gov (United States)

    Estrada, Ernesto; Kalala-Mutombo, Franck; Valverde-Colmeiro, Alba

    2011-09-01

    An "infection," understood here in a very broad sense, can be propagated through the network of social contacts among individuals. These social contacts include both "close" contacts and "casual" encounters among individuals in transport, leisure, shopping, etc. Knowing the first through the study of the social networks is not a difficult task, but having a clear picture of the network of casual contacts is a very hard problem in a society of increasing mobility. Here we assume, on the basis of several pieces of empirical evidence, that the casual contacts between two individuals are a function of their social distance in the network of close contacts. Then, we assume that we know the network of close contacts and infer the casual encounters by means of nonrandom long-range (LR) interactions determined by the social proximity of the two individuals. This approach is then implemented in a susceptible-infected-susceptible (SIS) model accounting for the spread of infections in complex networks. A parameter called "conductance" controls the feasibility of those casual encounters. In a zero conductance network only contagion through close contacts is allowed. As the conductance increases the probability of having casual encounters also increases. We show here that as the conductance parameter increases, the rate of propagation increases dramatically and the infection is less likely to die out. This increment is particularly marked in networks with scale-free degree distributions, where infections easily become epidemics. Our model provides a general framework for studying epidemic spreading in networks with arbitrary topology with and without casual contacts accounted for by means of LR interactions.

  3. Synchronization and Inter-Layer Interactions of Noise-Driven Neural Networks.

    Science.gov (United States)

    Yuniati, Anis; Mai, Te-Lun; Chen, Chi-Ming

    2017-01-01

    In this study, we used the Hodgkin-Huxley (HH) model of neurons to investigate the phase diagram of a developing single-layer neural network and that of a network consisting of two weakly coupled neural layers. These networks are noise driven and learn through the spike-timing-dependent plasticity (STDP) or the inverse STDP rules. We described how these networks transited from a non-synchronous background activity state (BAS) to a synchronous firing state (SFS) by varying the network connectivity and the learning efficacy. In particular, we studied the interaction between a SFS layer and a BAS layer, and investigated how synchronous firing dynamics was induced in the BAS layer. We further investigated the effect of the inter-layer interaction on a BAS to SFS repair mechanism by considering three types of neuron positioning (random, grid, and lognormal distributions) and two types of inter-layer connections (random and preferential connections). Among these scenarios, we concluded that the repair mechanism has the largest effect for a network with the lognormal neuron positioning and the preferential inter-layer connections.

  4. Topology and weights in a protein domain interaction network – a novel way to predict protein interactions

    Directory of Open Access Journals (Sweden)

    Wuchty Stefan

    2006-05-01

    Full Text Available Abstract Background While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. Results We consider a web of interactions between protein domains of the Protein Family database (PFAM, which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Conclusion Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we

  5. Development of Attention Networks and Their Interactions in Childhood

    Science.gov (United States)

    Pozuelos, Joan P.; Paz-Alonso, Pedro M.; Castillo, Alejandro; Fuentes, Luis J.; Rueda, M. Rosario

    2014-01-01

    In the present study, we investigated developmental trajectories of alerting, orienting, and executive attention networks and their interactions over childhood. Two cross-sectional experiments were conducted with different samples of 6-to 12-year-old children using modified versions of the attention network task (ANT). In Experiment 1 (N = 106),…

  6. Synchronization unveils the organization of ecological networks with positive and negative interactions

    Science.gov (United States)

    Girón, Andrea; Saiz, Hugo; Bacelar, Flora S.; Andrade, Roberto F. S.; Gómez-Gardeñes, Jesús

    2016-06-01

    Network science has helped to understand the organization principles of the interactions among the constituents of large complex systems. However, recently, the high resolution of the data sets collected has allowed to capture the different types of interactions coexisting within the same system. A particularly important example is that of systems with positive and negative interactions, a usual feature appearing in social, neural, and ecological systems. The interplay of links of opposite sign presents natural difficulties for generalizing typical concepts and tools applied to unsigned networks and, moreover, poses some questions intrinsic to the signed nature of the network, such as how are negative interactions balanced by positive ones so to allow the coexistence and survival of competitors/foes within the same system? Here, we show that synchronization phenomenon is an ideal benchmark for uncovering such balance and, as a byproduct, to assess which nodes play a critical role in the overall organization of the system. We illustrate our findings with the analysis of synthetic and real ecological networks in which facilitation and competitive interactions coexist.

  7. Synchronization unveils the organization of ecological networks with positive and negative interactions.

    Science.gov (United States)

    Girón, Andrea; Saiz, Hugo; Bacelar, Flora S; Andrade, Roberto F S; Gómez-Gardeñes, Jesús

    2016-06-01

    Network science has helped to understand the organization principles of the interactions among the constituents of large complex systems. However, recently, the high resolution of the data sets collected has allowed to capture the different types of interactions coexisting within the same system. A particularly important example is that of systems with positive and negative interactions, a usual feature appearing in social, neural, and ecological systems. The interplay of links of opposite sign presents natural difficulties for generalizing typical concepts and tools applied to unsigned networks and, moreover, poses some questions intrinsic to the signed nature of the network, such as how are negative interactions balanced by positive ones so to allow the coexistence and survival of competitors/foes within the same system? Here, we show that synchronization phenomenon is an ideal benchmark for uncovering such balance and, as a byproduct, to assess which nodes play a critical role in the overall organization of the system. We illustrate our findings with the analysis of synthetic and real ecological networks in which facilitation and competitive interactions coexist.

  8. State of Georgia AIP implementation report. Progress report, January--March 1996

    International Nuclear Information System (INIS)

    Hardeman, J.

    1996-01-01

    To ensure the citizens of the State of Georgia that health, safety and the environment are being protected through existing DOE programs at the Savannah River Site (SRS), through a vigorous program of independent monitoring and oversight by Georgia officials. This report summarizes implementation of this program from January to March 1996

  9. Raw materials exploitation in Prehistory of Georgia: sourcing, processing and distribution

    Science.gov (United States)

    Tushabramishvili, Nikoloz; Oqrostsvaridze, Avthandil

    2016-04-01

    Study of raw materials has a big importance to understand the ecology, cognition, behavior, technology, culture of the Paleolithic human populations. Unfortunately, explorations of the sourcing, processing and distribution of stone raw materials had a less attention until the present days. The reasons of that were: incomplete knowledge of the archaeologists who are doing the late period archaeology (Bronze Age-Medieval) and who are little bit far from the Paleolithic technology and typology; Ignorance of the stone artifacts made on different kind of raw-materials, except flint and obsidians. Studies on the origin of the stone raw materials are becoming increasingly important since in our days. Interesting picture and situation have been detected on the different sites and in different regions of Georgia. In earlier stages of Middle Paleolithic of Djruchula Basin caves the number of basalt, andesite, argillite etc. raw materials are quite big. Since 130 000 a percent of the flint raw-material is increasing dramatically. Flint is an almost lonely dominated raw-material in Western Georgia during thousand years. Since approximately 50 000 ago the first obsidians brought from the South Georgia, appeared in Western Georgia. Similar situation has been detected by us in Eastern Georgia during our excavations of Ziari and Pkhoveli open-air sites. The early Lower Paleolithic layers are extremely rich by limestone artifacts while the flint raw-materials are dominated in the Middle Paleolithic layers. Study of these issues is possible to achieve across chronologies, the origins of the sources of raw-materials, the sites and regions. By merging archaeology with anthropology, geology and geography we are able to acquire outstanding insights about those populations. New approach to the Paleolithic stone materials, newly found Paleolithic quarries gave us an opportunities to try to achieve some results for understanding of the behavior of Paleolithic populations, geology and

  10. Improving functional modules discovery by enriching interaction networks with gene profiles

    KAUST Repository

    Salem, Saeed

    2013-05-01

    Recent advances in proteomic and transcriptomic technologies resulted in the accumulation of vast amount of high-throughput data that span multiple biological processes and characteristics in different organisms. Much of the data come in the form of interaction networks and mRNA expression arrays. An important task in systems biology is functional modules discovery where the goal is to uncover well-connected sub-networks (modules). These discovered modules help to unravel the underlying mechanisms of the observed biological processes. While most of the existing module discovery methods use only the interaction data, in this work we propose, CLARM, which discovers biological modules by incorporating gene profiles data with protein-protein interaction networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional module discovery methods.

  11. Bird-plant interaction networks: a study on frugivory in Brazilian urban areas

    Directory of Open Access Journals (Sweden)

    Diego Silva Freitas Oliveira

    2015-12-01

    Full Text Available In Brazil, few studies compare the consumption of native and exotic fruits, especially in an urban environment. The Network Theory may be useful in such studies, because it allows evaluating many bird and plant species involved in interactions. The goals of this study were: evaluate a bird frugivory interaction network in an urban environment; checking the role played by native and exotic plants in the network and comparing the consumer assemblies of these two plant groups. A literature review on bird frugivory in Brazilian urban areas was conducted, as well as an analysis to create an interaction network on a regional scale. The analysis included 15 papers with 70 bird species eating fruits from 15 plant species (6 exotic and 9 native. The exotic and native fruit consumers did not form different groups and the interaction network was significantly nested (NODF = 0.30; p < 0.01 and not modular (M = 0.36; p = 0.16. Two exotic plant species are in the generalist core of the frugivory network (Ficus microcarpa and Michelia champaca. The results point out that a relatively diversified bird group eats fruits in Brazilian urban areas in an opportunistic way, with no preference for native or exotic plants.

  12. Groundwater conditions in Georgia, 2010–2011

    Science.gov (United States)

    Peck, Michael F.; Gordon, Debbie W.; Painter, Jaime A.

    2013-01-01

    The U.S. Geological Survey collects groundwater data and conducts studies to monitor hydrologic conditions, better define groundwater resources, and address problems related to water supply, water use, and water quality. In Georgia, water levels were monitored continuously at 186 wells during calendar year 2010 and at 181 wells during calendar year 2011. Because of missing data or short periods of record (less than 3 years) for several of these wells, a total of 168 wells are discussed in this report. These wells include 17 in the surficial aquifer system, 19 in the Brunswick aquifer system and equivalent sediments, 70 in the Upper Floridan aquifer, 16 in the Lower Floridan aquifer and underlying units, 10 in the Claiborne aquifer, 1 in the Gordon aquifer, 11 in the Clayton aquifer, 14 in the Cretaceous aquifer system, 2 in Paleozoic-rock aquifers, and 8 in crystalline-rock aquifers. Data from the well network indicate that water levels generally declined during the 2010 through 2011 calendar-year period, with water levels declining in 158 wells and rising in 10. Water levels declined over the period of record at 106 wells, increased at 56 wells, and remained relatively constant at 6 wells. In addition to continuous water-level data, periodic water-level measurements were collected and used to construct potentiometric-surface maps for the Upper Floridan aquifer in Camden, Charlton, and Ware Counties, Georgia, and adjacent counties in Florida during May–June 2010, and in the following areas in Georgia: the Brunswick area during August 2010 and August 2011, in the Albany–Dougherty County area during November 2010 and November 2011, and in the Augusta–Richmond County area during October 2010 and August 2011. In general, water levels in these areas were lower during 2011 than during 2010; however, the configuration of the potentiometric surfaces in each of the areas showed little change. Groundwater quality in the Floridan aquifer system is monitored in the

  13. Defining the protein interaction network of human malaria parasite Plasmodium falciparum

    KAUST Repository

    Ramaprasad, Abhinay

    2012-02-01

    Malaria, caused by the protozoan parasite Plasmodium falciparum, affects around 225. million people yearly and a huge international effort is directed towards combating this grave threat to world health and economic development. Considerable advances have been made in malaria research triggered by the sequencing of its genome in 2002, followed by several high-throughput studies defining the malaria transcriptome and proteome. A protein-protein interaction (PPI) network seeks to trace the dynamic interactions between proteins, thereby elucidating their local and global functional relationships. Experimentally derived PPI network from high-throughput methods such as yeast two hybrid (Y2H) screens are inherently noisy, but combining these independent datasets by computational methods tends to give a greater accuracy and coverage. This review aims to discuss the computational approaches used till date to construct a malaria protein interaction network and to catalog the functional predictions and biological inferences made from analysis of the PPI network. © 2011 Elsevier Inc.

  14. Epidemic spreading in networks with nonrandom long-range interactions

    Science.gov (United States)

    Estrada, Ernesto; Kalala-Mutombo, Franck; Valverde-Colmeiro, Alba

    2011-09-01

    An “infection,” understood here in a very broad sense, can be propagated through the network of social contacts among individuals. These social contacts include both “close” contacts and “casual” encounters among individuals in transport, leisure, shopping, etc. Knowing the first through the study of the social networks is not a difficult task, but having a clear picture of the network of casual contacts is a very hard problem in a society of increasing mobility. Here we assume, on the basis of several pieces of empirical evidence, that the casual contacts between two individuals are a function of their social distance in the network of close contacts. Then, we assume that we know the network of close contacts and infer the casual encounters by means of nonrandom long-range (LR) interactions determined by the social proximity of the two individuals. This approach is then implemented in a susceptible-infected-susceptible (SIS) model accounting for the spread of infections in complex networks. A parameter called “conductance” controls the feasibility of those casual encounters. In a zero conductance network only contagion through close contacts is allowed. As the conductance increases the probability of having casual encounters also increases. We show here that as the conductance parameter increases, the rate of propagation increases dramatically and the infection is less likely to die out. This increment is particularly marked in networks with scale-free degree distributions, where infections easily become epidemics. Our model provides a general framework for studying epidemic spreading in networks with arbitrary topology with and without casual contacts accounted for by means of LR interactions.

  15. The Global Alzheimer's Association Interactive Network.

    Science.gov (United States)

    Toga, Arthur W; Neu, Scott C; Bhatt, Priya; Crawford, Karen L; Ashish, Naveen

    2016-01-01

    The Global Alzheimer's Association Interactive Network (GAAIN) is consolidating the efforts of independent Alzheimer's disease data repositories around the world with the goals of revealing more insights into the causes of Alzheimer's disease, improving treatments, and designing preventative measures that delay the onset of physical symptoms. We developed a system for federating these repositories that is reliant on the tenets that (1) its participants require incentives to join, (2) joining the network is not disruptive to existing repository systems, and (3) the data ownership rights of its members are protected. We are currently in various phases of recruitment with over 55 data repositories in North America, Europe, Asia, and Australia and can presently query >250,000 subjects using GAAIN's search interfaces. GAAIN's data sharing philosophy, which guided our architectural choices, is conducive to motivating membership in a voluntary data sharing network. Copyright © 2016 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

  16. Personal Profiles: Enhancing Social Interaction in Learning Networks

    NARCIS (Netherlands)

    Berlanga, Adriana; Bitter-Rijpkema, Marlies; Brouns, Francis; Sloep, Peter; Fetter, Sibren

    2009-01-01

    Berlanga, A. J., Bitter-Rijpkema, M., Brouns, F., Sloep, P. B., & Fetter, S. (2011). Personal Profiles: Enhancing Social Interaction in Learning Networks. International Journal of Web Based Communities, 7(1), 66-82.

  17. Self-organization of social hierarchy on interaction networks

    International Nuclear Information System (INIS)

    Fujie, Ryo; Odagaki, Takashi

    2011-01-01

    In order to examine the effects of interaction network structures on the self-organization of social hierarchy, we introduce the agent-based model: each individual as on a node of a network has its own power and its internal state changes by fighting with its neighbors and relaxation. We adopt three different networks: regular lattice, small-world network and scale-free network. For the regular lattice, we find the emergence of classes distinguished by the internal state. The transition points where each class emerges are determined analytically, and we show that each class is characterized by the local ranking relative to their neighbors. We also find that the antiferromagnetic-like configuration emerges just above the critical point. For the heterogeneous networks, individuals become winners (or losers) in descending order of the number of their links. By using mean-field analysis, we reveal that the transition point is determined by the maximum degree and the degree distribution in its neighbors

  18. Network Graph Analysis of Gene-Gene Interactions in Genome-Wide Association Study Data

    Directory of Open Access Journals (Sweden)

    Sungyoung Lee

    2012-12-01

    Full Text Available Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs. For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR is one of the powerful and efficient methods for detecting high-order gene-gene (GxG interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI. Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

  19. Network graph analysis of gene-gene interactions in genome-wide association study data.

    Science.gov (United States)

    Lee, Sungyoung; Kwon, Min-Seok; Park, Taesung

    2012-12-01

    Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

  20. Network theory-based analysis of risk interactions in large engineering projects

    International Nuclear Information System (INIS)

    Fang, Chao; Marle, Franck; Zio, Enrico; Bocquet, Jean-Claude

    2012-01-01

    This paper presents an approach based on network theory to deal with risk interactions in large engineering projects. Indeed, such projects are exposed to numerous and interdependent risks of various nature, which makes their management more difficult. In this paper, a topological analysis based on network theory is presented, which aims at identifying key elements in the structure of interrelated risks potentially affecting a large engineering project. This analysis serves as a powerful complement to classical project risk analysis. Its originality lies in the application of some network theory indicators to the project risk management field. The construction of the risk network requires the involvement of the project manager and other team members assigned to the risk management process. Its interpretation improves their understanding of risks and their potential interactions. The outcomes of the analysis provide a support for decision-making regarding project risk management. An example of application to a real large engineering project is presented. The conclusion is that some new insights can be found about risks, about their interactions and about the global potential behavior of the project. - Highlights: ► The method addresses the modeling of complexity in project risk analysis. ► Network theory indicators enable other risks than classical criticality analysis to be highlighted. ► This topological analysis improves project manager's understanding of risks and risk interactions. ► This helps project manager to make decisions considering the position in the risk network. ► An application to a real tramway implementation project in a city is provided.

  1. Exploring hierarchical and overlapping modular structure in the yeast protein interaction network

    Directory of Open Access Journals (Sweden)

    Zhao Yi

    2010-12-01

    Full Text Available Abstract Background Developing effective strategies to reveal modular structures in protein interaction networks is crucial for better understanding of molecular mechanisms of underlying biological processes. In this paper, we propose a new density-based algorithm (ADHOC for clustering vertices of a protein interaction network using a novel subgraph density measurement. Results By statistically evaluating several independent criteria, we found that ADHOC could significantly improve the outcome as compared with five previously reported density-dependent methods. We further applied ADHOC to investigate the hierarchical and overlapping modular structure in the yeast PPI network. Our method could effectively detect both protein modules and the overlaps between them, and thus greatly promote the precise prediction of protein functions. Moreover, by further assaying the intermodule layer of the yeast PPI network, we classified hubs into two types, module hubs and inter-module hubs. Each type presents distinct characteristics both in network topology and biological functions, which could conduce to the better understanding of relationship between network architecture and biological implications. Conclusions Our proposed algorithm based on the novel subgraph density measurement makes it possible to more precisely detect hierarchical and overlapping modular structures in protein interaction networks. In addition, our method also shows a strong robustness against the noise in network, which is quite critical for analyzing such a high noise network.

  2. Strait of Georgia chinook and coho fishery

    National Research Council Canada - National Science Library

    Argue, A. W

    1983-01-01

    The chinook (Oncorhynchus tshawytscha) and coho (O. kisutch) salmon fishery in the Strait of Georgia, between Vancouver Island and the mainland of British Columbia, is a valuble sport and commercial resource...

  3. The Implementation and Results of the Use of Social Media in the Republic of Georgia

    Directory of Open Access Journals (Sweden)

    George Griffin

    2014-03-01

    Full Text Available 72 The Republic of Georgia has begun a transition from old world economics to integrating social media and the Internet to provide a global presence for the country. Research shows that the Georgian people have significantly embraced social media as a means for conducting business and connecting with many countries on a global basis. Internet subscribers have continually increased in numbers; thus the numbers of social media participants has also increased. This paper addresses the history of Georgia, the current status of social media in Georgia, and the future for social media as it permeates the Georgian population. In order to maintain a robust economic recovery, Georgia citizens and businesses must continue to conduct business through social media pathways that will keep Georgia in the global market. Normal 0 false false false EN-US X-NONE X-NONE

  4. Evolution of quantum and classical strategies on networks by group interactions

    International Nuclear Information System (INIS)

    Li Qiang; Chen Minyou; Iqbal, Azhar; Abbott, Derek

    2012-01-01

    In this paper, quantum strategies are introduced within evolutionary games in order to investigate the evolution of quantum and classical strategies on networks in the public goods game. Comparing the results of evolution on a scale-free network and a square lattice, we find that a quantum strategy outperforms the classical strategies, regardless of the network. Moreover, a quantum strategy dominates the population earlier in group interactions than it does in pairwise interactions. In particular, if the hub node in a scale-free network is occupied by a cooperator initially, the strategy of cooperation will prevail in the population. However, in other situations, a quantum strategy can defeat the classical ones and finally becomes the dominant strategy in the population. (paper)

  5. 76 FR 79192 - Patient Safety Organizations: Voluntary Relinquishment From the Georgia Hospital Association...

    Science.gov (United States)

    2011-12-21

    ... Organizations: Voluntary Relinquishment From the Georgia Hospital Association Research and Education Foundation Patient Safety Organization (GHA-PSO) AGENCY: Agency for Healthcare Research and Quality (AHRQ), HHS... The Georgia Hospital Association Research and Education Foundation Patient Safety Organization (GHA...

  6. Georgia Department of Transportation (GDOT) leadership academy.

    Science.gov (United States)

    2014-01-01

    Public agencies like the Georgia Department of Transportation (GDOT) are continually challenged with : reduced staff levels, reduced budgets, increased workloads and expectations for services provided. In : addition, the current economic and politica...

  7. Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases

    Directory of Open Access Journals (Sweden)

    Ma'ayan Avi

    2007-10-01

    Full Text Available Abstract Background In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP, generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Results Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Conclusion Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

  8. A human protein interaction network shows conservation of aging processes between human and invertebrate species.

    Directory of Open Access Journals (Sweden)

    Russell Bell

    2009-03-01

    Full Text Available We have mapped a protein interaction network of human homologs of proteins that modify longevity in invertebrate species. This network is derived from a proteome-scale human protein interaction Core Network generated through unbiased high-throughput yeast two-hybrid searches. The longevity network is composed of 175 human homologs of proteins known to confer increased longevity through loss of function in yeast, nematode, or fly, and 2,163 additional human proteins that interact with these homologs. Overall, the network consists of 3,271 binary interactions among 2,338 unique proteins. A comparison of the average node degree of the human longevity homologs with random sets of proteins in the Core Network indicates that human homologs of longevity proteins are highly connected hubs with a mean node degree of 18.8 partners. Shortest path length analysis shows that proteins in this network are significantly more connected than would be expected by chance. To examine the relationship of this network to human aging phenotypes, we compared the genes encoding longevity network proteins to genes known to be changed transcriptionally during aging in human muscle. In the case of both the longevity protein homologs and their interactors, we observed enrichments for differentially expressed genes in the network. To determine whether homologs of human longevity interacting proteins can modulate life span in invertebrates, homologs of 18 human FRAP1 interacting proteins showing significant changes in human aging muscle were tested for effects on nematode life span using RNAi. Of 18 genes tested, 33% extended life span when knocked-down in Caenorhabditis elegans. These observations indicate that a broad class of longevity genes identified in invertebrate models of aging have relevance to human aging. They also indicate that the longevity protein interaction network presented here is enriched for novel conserved longevity proteins.

  9. The Programs for Strengthening Biosafety and Biosecurity in Georgia

    International Nuclear Information System (INIS)

    Kutateladze, M.

    2007-01-01

    The difficulties connected with the political changes due to the breakdown of Soviet system caused serious problems in biosafety and security in Georgia. During last 10-12 years, lack of state financing caused destruction of the systems of biosafety in the relevant Institutions - the system became formal and completely damaged. The program for prevention of biological weapons (BW) proliferation operates in Georgia since 2002. The agreement between United States and Georgia covers several issues, including prevention the proliferation of biological weapons technology, pathogenic strains and their expertise at the source. Department of Defense of the USA supports the country to consolidate especially dangerous pathogens (EDPs) into safe and secure central reference laboratories, improve our capabilities to detect and respond to disease outbreaks caused by the EDP, integrate Georgian scientists into the international scientific community and eliminate BW infrastructure and technology. Elimination of BW infrastructure includes dismantle and elimination of biological threat agent materials, dual-use equipment and associated infrastructure. Biosecurity and Biosafety involve implementation of technical enhancements to meet and maintain US standards, create a personal reliability program to reduce the release of pathogens and secure a safer working environment for personnel. Currently, two projects are funded through the Cooperative Biological Research (CBR) in Georgia - to study the ecology, biodiversity, genetic clustering and virulence of Yersinia pestis and Vibrio spp. These projects are performed at the National Center for Disease Control and Medical statistics (NCDC) and G. Eliava Institute of Bacteriophages, Microbiology and Virology. These projects are carried out due to the fruitful collaboration between Georgian and American scientists. Threat Agent Detection and Response (TADR) system provides enhanced reporting, detection and response for human and animal EDPs

  10. Bilingual Lexical Interactions in an Unsupervised Neural Network Model

    Science.gov (United States)

    Zhao, Xiaowei; Li, Ping

    2010-01-01

    In this paper we present an unsupervised neural network model of bilingual lexical development and interaction. We focus on how the representational structures of the bilingual lexicons can emerge, develop, and interact with each other as a function of the learning history. The results show that: (1) distinct representations for the two lexicons…

  11. Analysis of protein-protein interaction networks by means of annotated graph mining algorithms

    NARCIS (Netherlands)

    Rahmani, Hossein

    2012-01-01

    This thesis discusses solutions to several open problems in Protein-Protein Interaction (PPI) networks with the aid of Knowledge Discovery. PPI networks are usually represented as undirected graphs, with nodes corresponding to proteins and edges representing interactions among protein pairs. A large

  12. Hepatitis C Virus Protein Interaction Network Analysis Based on Hepatocellular Carcinoma.

    Directory of Open Access Journals (Sweden)

    Yuewen Han

    Full Text Available Epidemiological studies have validated the association between hepatitis C virus (HCV infection and hepatocellular carcinoma (HCC. An increasing number of studies show that protein-protein interactions (PPIs between HCV proteins and host proteins play a vital role in infection and mediate HCC progression. In this work, we collected all published interaction between HCV and human proteins, which include 455 unique human proteins participating in 524 HCV-human interactions. Then, we construct the HCV-human and HCV-HCC protein interaction networks, which display the biological knowledge regarding the mechanism of HCV pathogenesis, particularly with respect to pathogenesis of HCC. Through in-depth analysis of the HCV-HCC interaction network, we found that interactors are enriched in the JAK/STAT, p53, MAPK, TNF, Wnt, and cell cycle pathways. Using a random walk with restart algorithm, we predicted the importance of each protein in the HCV-HCC network and found that AKT1 may play a key role in the HCC progression. Moreover, we found that NS5A promotes HCC cells proliferation and metastasis by activating AKT/GSK3β/β-catenin pathway. This work provides a basis for a detailed map tracking new cellular interactions of HCV and identifying potential targets for HCV-related hepatocellular carcinoma treatment.

  13. Dynamical analysis of yeast protein interaction network during the sake brewing process.

    Science.gov (United States)

    Mirzarezaee, Mitra; Sadeghi, Mehdi; Araabi, Babak N

    2011-12-01

    Proteins interact with each other for performing essential functions of an organism. They change partners to get involved in various processes at different times or locations. Studying variations of protein interactions within a specific process would help better understand the dynamic features of the protein interactions and their functions. We studied the protein interaction network of Saccharomyces cerevisiae (yeast) during the brewing of Japanese sake. In this process, yeast cells are exposed to several stresses. Analysis of protein interaction networks of yeast during this process helps to understand how protein interactions of yeast change during the sake brewing process. We used gene expression profiles of yeast cells for this purpose. Results of our experiments revealed some characteristics and behaviors of yeast hubs and non-hubs and their dynamical changes during the brewing process. We found that just a small portion of the proteins (12.8 to 21.6%) is responsible for the functional changes of the proteins in the sake brewing process. The changes in the number of edges and hubs of the yeast protein interaction networks increase in the first stages of the process and it then decreases at the final stages.

  14. In silico modeling of the yeast protein and protein family interaction network

    Science.gov (United States)

    Goh, K.-I.; Kahng, B.; Kim, D.

    2004-03-01

    Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.

  15. Network Analysis Reveals a Common Host–Pathogen Interaction Pattern in Arabidopsis Immune Responses

    Directory of Open Access Journals (Sweden)

    Hong Li

    2017-05-01

    Full Text Available Many plant pathogens secrete virulence effectors into host cells to target important proteins in host cellular network. However, the dynamic interactions between effectors and host cellular network have not been fully understood. Here, an integrative network analysis was conducted by combining Arabidopsis thaliana protein–protein interaction network, known targets of Pseudomonas syringae and Hyaloperonospora arabidopsidis effectors, and gene expression profiles in the immune response. In particular, we focused on the characteristic network topology of the effector targets and differentially expressed genes (DEGs. We found that effectors tended to manipulate key network positions with higher betweenness centrality. The effector targets, especially those that are common targets of an individual effector, tended to be clustered together in the network. Moreover, the distances between the effector targets and DEGs increased over time during infection. In line with this observation, pathogen-susceptible mutants tended to have more DEGs surrounding the effector targets compared with resistant mutants. Our results suggest a common plant–pathogen interaction pattern at the cellular network level, where pathogens employ potent local impact mode to interfere with key positions in the host network, and plant organizes an in-depth defense by sequentially activating genes distal to the effector targets.

  16. Legislative Update: Georgia School Funding Update.

    Science.gov (United States)

    Holmes, C. Thomas; Sielke, Catherine C.

    2000-01-01

    Fully 40 percent ($5 billion) of Georgia's FY 2000 general funds budget is for K-12 education. There is increased funding for a homestead exemption, expansion of the HOPE (higher education) Scholarship Program, capital outlay projects, remedial assistance programs, and instruction of limited-English speaking students. (MLH)

  17. The problems of nuclear security in Georgia

    International Nuclear Information System (INIS)

    Nabakhtiani, N.

    2006-01-01

    Georgia is carrying out activities to improve nuclear security according to the demands of international standards and rules. The support of developed countries and international organisations is very important to solve the associated problems. (author)

  18. Reconstruction and validation of RefRec: a global model for the yeast molecular interaction network.

    Directory of Open Access Journals (Sweden)

    Tommi Aho

    2010-05-01

    Full Text Available Molecular interaction networks establish all cell biological processes. The networks are under intensive research that is facilitated by new high-throughput measurement techniques for the detection, quantification, and characterization of molecules and their physical interactions. For the common model organism yeast Saccharomyces cerevisiae, public databases store a significant part of the accumulated information and, on the way to better understanding of the cellular processes, there is a need to integrate this information into a consistent reconstruction of the molecular interaction network. This work presents and validates RefRec, the most comprehensive molecular interaction network reconstruction currently available for yeast. The reconstruction integrates protein synthesis pathways, a metabolic network, and a protein-protein interaction network from major biological databases. The core of the reconstruction is based on a reference object approach in which genes, transcripts, and proteins are identified using their primary sequences. This enables their unambiguous identification and non-redundant integration. The obtained total number of different molecular species and their connecting interactions is approximately 67,000. In order to demonstrate the capacity of RefRec for functional predictions, it was used for simulating the gene knockout damage propagation in the molecular interaction network in approximately 590,000 experimentally validated mutant strains. Based on the simulation results, a statistical classifier was subsequently able to correctly predict the viability of most of the strains. The results also showed that the usage of different types of molecular species in the reconstruction is important for accurate phenotype prediction. In general, the findings demonstrate the benefits of global reconstructions of molecular interaction networks. With all the molecular species and their physical interactions explicitly modeled, our

  19. PREVALENCE OF CLEFT LIP AND PALATE IN GEORGIA.

    Science.gov (United States)

    Chincharadze, S; Vadachkoria, Z; Mchedlishvili, I

    2017-01-01

    Cleft lip and palate take significant place in congenital malformations. We aimed to study epidemiological peculiarities of these pathologies in Georgia for 2006-2015. We compared magnitude of its distribution with the data from 1981-1990. Prevalence of cleft lip and palate in Georgia in 2006-2015 was 0.95±0.04 per 1000 live births, while in 1981-1990- it was 1.05, i.e. in contrast to 1980's frequency of these pathological conditions decreased to some extent. Distribution of cleft lip and palate varies across the country regions. The most intensive spread has been observed in Mtskheta-Mtianeti region, where prevalence composed 2.28/1000. In the rest of the regions frequency of these pathologies is significantly lower. For instance, in Kakheti the rate is equal to 1,87/1000, in Kvemo Kartli - 1.56/1000, in Shida Kartli - 1.55/1000. In the rest of the regions prevalence rate is lower than the country average. It should be noted that in Tbilisi the rate is as low as 0.80/1000. The lowest level has been reported in Guria - 0.56/1000. Currently cleft lip with palate is the most frequently occurring anomaly in Georgia accounting for 39.8% of all congenital malformations. Cleft lip alone ranks the second - 36.1%, followed by cleft palate (24.1%). These pathologies are more frequent in boys than in girls. 60.3% of the cases are reported in males, in contrast to girls - 39.7% (pcleft palate is the most common among girls, but in our case, it had higher prevalence among boys, 53.6% vs. 46,4%. Thus cleft lip and palate distribution in Georgia is characterized by epidemiological peculiarities, which should be considered in implementation of preventive measures.

  20. Interactions of the Salience Network and Its Subsystems with the Default-Mode and the Central-Executive Networks in Normal Aging and Mild Cognitive Impairment.

    Science.gov (United States)

    Chand, Ganesh B; Wu, Junjie; Hajjar, Ihab; Qiu, Deqiang

    2017-09-01

    Previous functional magnetic resonance imaging (fMRI) investigations suggest that the intrinsically organized large-scale networks and the interaction between them might be crucial for cognitive activities. A triple network model, which consists of the default-mode network, salience network, and central-executive network, has been recently used to understand the connectivity patterns of the cognitively normal brains versus the brains with disorders. This model suggests that the salience network dynamically controls the default-mode and central-executive networks in healthy young individuals. However, the patterns of interactions have remained largely unknown in healthy aging or those with cognitive decline. In this study, we assess the patterns of interactions between the three networks using dynamical causal modeling in resting state fMRI data and compare them between subjects with normal cognition and mild cognitive impairment (MCI). In healthy elderly subjects, our analysis showed that the salience network, especially its dorsal subnetwork, modulates the interaction between the default-mode network and the central-executive network (Mann-Whitney U test; p control correlated significantly with lower overall cognitive performance measured by Montreal Cognitive Assessment (r = 0.295; p control, especially the dorsal salience network, over other networks provides a neuronal basis for cognitive decline and may be a candidate neuroimaging biomarker of cognitive impairment.

  1. 3DProIN: Protein-Protein Interaction Networks and Structure Visualization.

    Science.gov (United States)

    Li, Hui; Liu, Chunmei

    2014-06-14

    3DProIN is a computational tool to visualize protein-protein interaction networks in both two dimensional (2D) and three dimensional (3D) view. It models protein-protein interactions in a graph and explores the biologically relevant features of the tertiary structures of each protein in the network. Properties such as color, shape and name of each node (protein) of the network can be edited in either 2D or 3D views. 3DProIN is implemented using 3D Java and C programming languages. The internet crawl technique is also used to parse dynamically grasped protein interactions from protein data bank (PDB). It is a java applet component that is embedded in the web page and it can be used on different platforms including Linux, Mac and Window using web browsers such as Firefox, Internet Explorer, Chrome and Safari. It also was converted into a mac app and submitted to the App store as a free app. Mac users can also download the app from our website. 3DProIN is available for academic research at http://bicompute.appspot.com.

  2. Forest statistics for Georgia, 1982

    Science.gov (United States)

    John E. Tansey

    1983-01-01

    Since the fourth inventory of the forest resources of Georgia in 1972, the area of commercial forest land decreased over 4 percent, or by almost 1.1 million acres. Commercial forests now cover approximately 23.7 million acres, 64 percent of the land area in the State. Nearly 5.1 million acres were harvested, while about 2.9 million acres were adequately regenerated...

  3. 2012 Oconee County, Georgia ADS80 Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — All imagery was collected during the 2012 Spring flying season during leaf-off conditions for deciduous vegetation in the State of Georgia. The sun angle was at...

  4. Discovering disease-associated genes in weighted protein-protein interaction networks

    Science.gov (United States)

    Cui, Ying; Cai, Meng; Stanley, H. Eugene

    2018-04-01

    Although there have been many network-based attempts to discover disease-associated genes, most of them have not taken edge weight - which quantifies their relative strength - into consideration. We use connection weights in a protein-protein interaction (PPI) network to locate disease-related genes. We analyze the topological properties of both weighted and unweighted PPI networks and design an improved random forest classifier to distinguish disease genes from non-disease genes. We use a cross-validation test to confirm that weighted networks are better able to discover disease-associated genes than unweighted networks, which indicates that including link weight in the analysis of network properties provides a better model of complex genotype-phenotype associations.

  5. Context-specific protein network miner - an online system for exploring context-specific protein interaction networks from the literature

    KAUST Repository

    Chowdhary, Rajesh

    2012-04-06

    Background: Protein interaction networks (PINs) specific within a particular context contain crucial information regarding many cellular biological processes. For example, PINs may include information on the type and directionality of interaction (e.g. phosphorylation), location of interaction (i.e. tissues, cells), and related diseases. Currently, very few tools are capable of deriving context-specific PINs for conducting exploratory analysis. Results: We developed a literature-based online system, Context-specific Protein Network Miner (CPNM), which derives context-specific PINs in real-time from the PubMed database based on a set of user-input keywords and enhanced PubMed query system. CPNM reports enriched information on protein interactions (with type and directionality), their network topology with summary statistics (e.g. most densely connected proteins in the network; most densely connected protein-pairs; and proteins connected by most inbound/outbound links) that can be explored via a user-friendly interface. Some of the novel features of the CPNM system include PIN generation, ontology-based PubMed query enhancement, real-time, user-queried, up-to-date PubMed document processing, and prediction of PIN directionality. Conclusions: CPNM provides a tool for biologists to explore PINs. It is freely accessible at http://www.biotextminer.com/CPNM/. © 2012 Chowdhary et al.

  6. Context-specific protein network miner - an online system for exploring context-specific protein interaction networks from the literature

    KAUST Repository

    Chowdhary, Rajesh; Tan, Sin Lam; Zhang, Jinfeng; Karnik, Shreyas; Bajic, Vladimir B.; Liu, Jun S.

    2012-01-01

    Background: Protein interaction networks (PINs) specific within a particular context contain crucial information regarding many cellular biological processes. For example, PINs may include information on the type and directionality of interaction (e.g. phosphorylation), location of interaction (i.e. tissues, cells), and related diseases. Currently, very few tools are capable of deriving context-specific PINs for conducting exploratory analysis. Results: We developed a literature-based online system, Context-specific Protein Network Miner (CPNM), which derives context-specific PINs in real-time from the PubMed database based on a set of user-input keywords and enhanced PubMed query system. CPNM reports enriched information on protein interactions (with type and directionality), their network topology with summary statistics (e.g. most densely connected proteins in the network; most densely connected protein-pairs; and proteins connected by most inbound/outbound links) that can be explored via a user-friendly interface. Some of the novel features of the CPNM system include PIN generation, ontology-based PubMed query enhancement, real-time, user-queried, up-to-date PubMed document processing, and prediction of PIN directionality. Conclusions: CPNM provides a tool for biologists to explore PINs. It is freely accessible at http://www.biotextminer.com/CPNM/. © 2012 Chowdhary et al.

  7. Minimum curvilinearity to enhance topological prediction of protein interactions by network embedding

    KAUST Repository

    Cannistraci, Carlo

    2013-06-21

    Motivation: Most functions within the cell emerge thanks to protein-protein interactions (PPIs), yet experimental determination of PPIs is both expensive and time-consuming. PPI networks present significant levels of noise and incompleteness. Predicting interactions using only PPI-network topology (topological prediction) is difficult but essential when prior biological knowledge is absent or unreliable.Methods: Network embedding emphasizes the relations between network proteins embedded in a low-dimensional space, in which protein pairs that are closer to each other represent good candidate interactions. To achieve network denoising, which boosts prediction performance, we first applied minimum curvilinear embedding (MCE), and then adopted shortest path (SP) in the reduced space to assign likelihood scores to candidate interactions. Furthermore, we introduce (i) a new valid variation of MCE, named non-centred MCE (ncMCE); (ii) two automatic strategies for selecting the appropriate embedding dimension; and (iii) two new randomized procedures for evaluating predictions.Results: We compared our method against several unsupervised and supervisedly tuned embedding approaches and node neighbourhood techniques. Despite its computational simplicity, ncMCE-SP was the overall leader, outperforming the current methods in topological link prediction.Conclusion: Minimum curvilinearity is a valuable non-linear framework that we successfully applied to the embedding of protein networks for the unsupervised prediction of novel PPIs. The rationale for our approach is that biological and evolutionary information is imprinted in the non-linear patterns hidden behind the protein network topology, and can be exploited for predicting new protein links. The predicted PPIs represent good candidates for testing in high-throughput experiments or for exploitation in systems biology tools such as those used for network-based inference and prediction of disease-related functional modules. The

  8. Systems pharmacology - Towards the modeling of network interactions.

    Science.gov (United States)

    Danhof, Meindert

    2016-10-30

    Mechanism-based pharmacokinetic and pharmacodynamics (PKPD) and disease system (DS) models have been introduced in drug discovery and development research, to predict in a quantitative manner the effect of drug treatment in vivo in health and disease. This requires consideration of several fundamental properties of biological systems behavior including: hysteresis, non-linearity, variability, interdependency, convergence, resilience, and multi-stationarity. Classical physiology-based PKPD models consider linear transduction pathways, connecting processes on the causal path between drug administration and effect, as the basis of drug action. Depending on the drug and its biological target, such models may contain expressions to characterize i) the disposition and the target site distribution kinetics of the drug under investigation, ii) the kinetics of target binding and activation and iii) the kinetics of transduction. When connected to physiology-based DS models, PKPD models can characterize the effect on disease progression in a mechanistic manner. These models have been found useful to characterize hysteresis and non-linearity, yet they fail to explain the effects of the other fundamental properties of biological systems behavior. Recently systems pharmacology has been introduced as novel approach to predict in vivo drug effects, in which biological networks rather than single transduction pathways are considered as the basis of drug action and disease progression. These models contain expressions to characterize the functional interactions within a biological network. Such interactions are relevant when drugs act at multiple targets in the network or when homeostatic feedback mechanisms are operative. As a result systems pharmacology models are particularly useful to describe complex patterns of drug action (i.e. synergy, oscillatory behavior) and disease progression (i.e. episodic disorders). In this contribution it is shown how physiology-based PKPD and

  9. The Geographic Reference Atlas of Georgia

    DEFF Research Database (Denmark)

    Liparteliani, Guliza; Kurtubadze, Manana; Sologhashvili, Nato

    2017-01-01

    of the exploration of the nature, population, economy and history of Georgia. Both, the first and the second atlases are scientific by the content, the purpose and the design. Nowadays, Georgian society requires to understand country not only from maps, but also from photos, related text annotations and graphic...

  10. Deregulation of natural gas in Georgia

    International Nuclear Information System (INIS)

    Wise, S.

    2002-01-01

    The Natural Gas Competition and Deregulation Act of 1997 in Georgia is discussed. New legislation passed the Natural Gas Consumer Relief Act in 2002 legislative session to provide additional protection and increase competition. This Act and its impacts are discussed in detail. Additional commission responsibilities are summarized. (R.P.)

  11. Protein-Protein Interaction Network and Gene Ontology

    Science.gov (United States)

    Choi, Yunkyu; Kim, Seok; Yi, Gwan-Su; Park, Jinah

    Evolution of computer technologies makes it possible to access a large amount and various kinds of biological data via internet such as DNA sequences, proteomics data and information discovered about them. It is expected that the combination of various data could help researchers find further knowledge about them. Roles of a visualization system are to invoke human abilities to integrate information and to recognize certain patterns in the data. Thus, when the various kinds of data are examined and analyzed manually, an effective visualization system is an essential part. One instance of these integrated visualizations can be combination of protein-protein interaction (PPI) data and Gene Ontology (GO) which could help enhance the analysis of PPI network. We introduce a simple but comprehensive visualization system that integrates GO and PPI data where GO and PPI graphs are visualized side-by-side and supports quick reference functions between them. Furthermore, the proposed system provides several interactive visualization methods for efficiently analyzing the PPI network and GO directedacyclic- graph such as context-based browsing and common ancestors finding.

  12. Protein complex prediction based on k-connected subgraphs in protein interaction network

    Directory of Open Access Journals (Sweden)

    Habibi Mahnaz

    2010-09-01

    Full Text Available Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on connectivity number on subgraphs. We evaluate CFA using several protein interaction networks on reference protein complexes in two benchmark data sets (MIPS and Aloy, containing 1142 and 61 known complexes respectively. We compare CFA to some existing protein complex prediction methods (CMC, MCL, PCP and RNSC in terms of recall and precision. We show that CFA predicts more complexes correctly at a competitive level of precision. Conclusions Many real complexes with different connectivity level in protein interaction network can be predicted based on connectivity number. Our CFA program and results are freely available from http://www.bioinf.cs.ipm.ir/softwares/cfa/CFA.rar.

  13. Limitations of a metabolic network-based reverse ecology method for inferring host-pathogen interactions.

    Science.gov (United States)

    Takemoto, Kazuhiro; Aie, Kazuki

    2017-05-25

    Host-pathogen interactions are important in a wide range of research fields. Given the importance of metabolic crosstalk between hosts and pathogens, a metabolic network-based reverse ecology method was proposed to infer these interactions. However, the validity of this method remains unclear because of the various explanations presented and the influence of potentially confounding factors that have thus far been neglected. We re-evaluated the importance of the reverse ecology method for evaluating host-pathogen interactions while statistically controlling for confounding effects using oxygen requirement, genome, metabolic network, and phylogeny data. Our data analyses showed that host-pathogen interactions were more strongly influenced by genome size, primary network parameters (e.g., number of edges), oxygen requirement, and phylogeny than the reserve ecology-based measures. These results indicate the limitations of the reverse ecology method; however, they do not discount the importance of adopting reverse ecology approaches altogether. Rather, we highlight the need for developing more suitable methods for inferring host-pathogen interactions and conducting more careful examinations of the relationships between metabolic networks and host-pathogen interactions.

  14. Visualization of protein interaction networks: problems and solutions

    Directory of Open Access Journals (Sweden)

    Agapito Giuseppe

    2013-01-01

    Full Text Available Abstract Background Visualization concerns the representation of data visually and is an important task in scientific research. Protein-protein interactions (PPI are discovered using either wet lab techniques, such mass spectrometry, or in silico predictions tools, resulting in large collections of interactions stored in specialized databases. The set of all interactions of an organism forms a protein-protein interaction network (PIN and is an important tool for studying the behaviour of the cell machinery. Since graphic representation of PINs may highlight important substructures, e.g. protein complexes, visualization is more and more used to study the underlying graph structure of PINs. Although graphs are well known data structures, there are different open problems regarding PINs visualization: the high number of nodes and connections, the heterogeneity of nodes (proteins and edges (interactions, the possibility to annotate proteins and interactions with biological information extracted by ontologies (e.g. Gene Ontology that enriches the PINs with semantic information, but complicates their visualization. Methods In these last years many software tools for the visualization of PINs have been developed. Initially thought for visualization only, some of them have been successively enriched with new functions for PPI data management and PIN analysis. The paper analyzes the main software tools for PINs visualization considering four main criteria: (i technology, i.e. availability/license of the software and supported OS (Operating System platforms; (ii interoperability, i.e. ability to import/export networks in various formats, ability to export data in a graphic format, extensibility of the system, e.g. through plug-ins; (iii visualization, i.e. supported layout and rendering algorithms and availability of parallel implementation; (iv analysis, i.e. availability of network analysis functions, such as clustering or mining of the graph, and the

  15. Interactive social contagions and co-infections on complex networks

    Science.gov (United States)

    Liu, Quan-Hui; Zhong, Lin-Feng; Wang, Wei; Zhou, Tao; Eugene Stanley, H.

    2018-01-01

    What we are learning about the ubiquitous interactions among multiple social contagion processes on complex networks challenges existing theoretical methods. We propose an interactive social behavior spreading model, in which two behaviors sequentially spread on a complex network, one following the other. Adopting the first behavior has either a synergistic or an inhibiting effect on the spread of the second behavior. We find that the inhibiting effect of the first behavior can cause the continuous phase transition of the second behavior spreading to become discontinuous. This discontinuous phase transition of the second behavior can also become a continuous one when the effect of adopting the first behavior becomes synergistic. This synergy allows the second behavior to be more easily adopted and enlarges the co-existence region of both behaviors. We establish an edge-based compartmental method, and our theoretical predictions match well with the simulation results. Our findings provide helpful insights into better understanding the spread of interactive social behavior in human society.

  16. Enhancement of a Virtual Geology Field Guide of Georgia Initiative Using Gigapan© and ArcGIS Online's Story Map

    Science.gov (United States)

    Mobasher, K.; Turk, H. J.; Witherspoon, W.; Tate, L.; Hoynes, J.

    2015-12-01

    A GIS geology geodatabase of Georgia was developed using ArcGIS 10.2. The geodatabase for each physiographic provinces of Georgia contains fields designed to store information regarding geologic features. Using ArcGIS online, the virtual field guide is created which provides an interactive learning experience for students to allow in real time photography, description, mapping and sharing their observations with the instructor and peers. Gigapan© facilitates visualizing geologic features at different scales with high resolutions and in their larger surrounding context. The classroom applications of the Gigapan© are limitless when teaching students the entire range of geologic structures from showcasing crystalline structures of minerals to understanding the geological processes responsible for formation of an entire mountain range. The addition of the Story Map enhances the virtual experience when you want to present a geo-located story point narrative featuring images or videos. The virtual field component and supplementary Gigapan© imagery coupled with Story Map added significantly to the detailed realism of virtual field guide further allowing students to more fully understand geological concepts at various scales. These technologies peaked students interest and facilitated their learning and preparation to function more effectively in the geosciences by developing better observations and new skills. These technologies facilitated increased student engagement in the geosciences by sharing, enhancing and transferring lecture information to actual field knowledge and experiences. This enhanced interactive learning experience not only begins to allow students to understand and recognize geologic features in the field but also increased their collaboration, enthusiasm and interest in the discipline. The increased interest and collaboration occurred as students assisted in populating a geologic geodatabase of Georgia.

  17. Changes in the interaction of resting-state neural networks from adolescence to adulthood.

    Science.gov (United States)

    Stevens, Michael C; Pearlson, Godfrey D; Calhoun, Vince D

    2009-08-01

    This study examined how the mutual interactions of functionally integrated neural networks during resting-state fMRI differed between adolescence and adulthood. Independent component analysis (ICA) was used to identify functionally connected neural networks in 100 healthy participants aged 12-30 years. Hemodynamic timecourses that represented integrated neural network activity were analyzed with tools that quantified system "causal density" estimates, which indexed the proportion of significant Granger causality relationships among system nodes. Mutual influences among networks decreased with age, likely reflecting stronger within-network connectivity and more efficient between-network influences with greater development. Supplemental tests showed that this normative age-related reduction in causal density was accompanied by fewer significant connections to and from each network, regional increases in the strength of functional integration within networks, and age-related reductions in the strength of numerous specific system interactions. The latter included paths between lateral prefrontal-parietal circuits and "default mode" networks. These results contribute to an emerging understanding that activity in widely distributed networks thought to underlie complex cognition influences activity in other networks. (c) 2009 Wiley-Liss, Inc.

  18. Financial Stability and Interacting Networks of Financial Institutions and Market Infrastructures

    NARCIS (Netherlands)

    Léon, C.; Berndsen, R.J.; Renneboog, L.D.R.

    2014-01-01

    An interacting network coupling financial institutions’ multiplex (i.e. multi-layer) and financial market infrastructures’ single-layer networks gives an accurate picture of a financial system’s true connective architecture. We examine and compare the main properties of Colombian multiplex and

  19. EAARL topography-Potato Creek watershed, Georgia, 2010

    Science.gov (United States)

    Bonisteel-Cormier, J.M.; Nayegandhi, Amar; Fredericks, Xan; Jones, J.W.; Wright, C.W.; Brock, J.C.; Nagle, D.B.

    2011-01-01

    This DVD contains lidar-derived first-surface (FS) and bare-earth (BE) topography GIS datasets of a portion of the Potato Creek watershed in the Apalachicola-Chattahoochee-Flint River basin, Georgia. These datasets were acquired on February 27, 2010.

  20. Georgia Species at Risk Project

    Science.gov (United States)

    2009-06-01

    Robins, ten at Fort Stewart, and three at King’s Bay. GA-DNR contracted with the Natural Resources Spatial Analysis Laboratory (NARSAL) to produce...stagnant, tannin -stained waters in creeks and impoundments, especially in areas with heavy aquatic vegetation (Hoover et al. 1998). A management...was contracted to the Natural Resources Spatial Analysis Laboratory (NARSAL) at the University of Georgia, who previously completed mapping at a

  1. Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

    Science.gov (United States)

    Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

    2015-01-01

    Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these

  2. Detection of Locally Over-Represented GO Terms in Protein-Protein Interaction Networks

    Science.gov (United States)

    LAVALLÉE-ADAM, MATHIEU; COULOMBE, BENOIT; BLANCHETTE, MATHIEU

    2015-01-01

    High-throughput methods for identifying protein-protein interactions produce increasingly complex and intricate interaction networks. These networks are extremely rich in information, but extracting biologically meaningful hypotheses from them and representing them in a human-readable manner is challenging. We propose a method to identify Gene Ontology terms that are locally over-represented in a subnetwork of a given biological network. Specifically, we propose several methods to evaluate the degree of clustering of proteins associated to a particular GO term in both weighted and unweighted PPI networks, and describe efficient methods to estimate the statistical significance of the observed clustering. We show, using Monte Carlo simulations, that our best approximation methods accurately estimate the true p-value, for random scale-free graphs as well as for actual yeast and human networks. When applied to these two biological networks, our approach recovers many known complexes and pathways, but also suggests potential functions for many subnetworks. Online Supplementary Material is available at www.liebertonline.com. PMID:20377456

  3. Preliminary assessment report for National Guard Training Center, Georgia Army National Guard, Fort Stewart, Georgia

    International Nuclear Information System (INIS)

    1993-07-01

    This report presents the results of the preliminary assessment (PA) conducted by Argonne National Laboratory at the Georgia Army National Guard (GAARNG) facility near Hinesville, Georgia, known as the National Guard Training Center (NGTC). Preliminary assessments of federal facilities are being conducted to compile the information necessary for completing preremedial activities and to provide a priority basis for completing corrective actions (where necessary) in response to releases of hazardous substances. The principal objective of the PA is to characterize the site accurately and determine the need for further action by examining previous site activities, types and quantities of hazardous substances utilized, and potential pathways by which contamination could affect public health and the environment. The scope of this assessment is limited to the facilities and past activities contained within the NGTC. Preliminary assessment site score sheet information is also provided for the NGTC. However, this assessment report is intended to be read in conjunction with a previous IRP assessment of Fort Stewart completed in 1992 (USATHAMA 1992) and to provide comprehensive information on the NGTC area for incorporation with information contained in that previous assessment for the entirety of Fort Stewart

  4. STITCH 2: an interaction network database for small molecules and proteins

    DEFF Research Database (Denmark)

    Kuhn, Michael; Szklarczyk, Damian; Franceschini, Andrea

    2010-01-01

    Over the last years, the publicly available knowledge on interactions between small molecules and proteins has been steadily increasing. To create a network of interactions, STITCH aims to integrate the data dispersed over the literature and various databases of biological pathways, drug......-target relationships and binding affinities. In STITCH 2, the number of relevant interactions is increased by incorporation of BindingDB, PharmGKB and the Comparative Toxicogenomics Database. The resulting network can be explored interactively or used as the basis for large-scale analyses. To facilitate links to other...... chemical databases, we adopt InChIKeys that allow identification of chemicals with a short, checksum-like string. STITCH 2.0 connects proteins from 630 organisms to over 74,000 different chemicals, including 2200 drugs. STITCH can be accessed at http://stitch.embl.de/....

  5. Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

    International Nuclear Information System (INIS)

    Ba, Qian; Li, Junyang; Huang, Chao; Li, Jingquan; Chu, Ruiai; Wu, Yongning; Wang, Hui

    2015-01-01

    Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong to the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified

  6. Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

    Energy Technology Data Exchange (ETDEWEB)

    Ba, Qian [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Li, Junyang; Huang, Chao [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Li, Jingquan; Chu, Ruiai [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wu, Yongning, E-mail: wuyongning@cfsa.net.cn [Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wang, Hui, E-mail: huiwang@sibs.ac.cn [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); School of Life Science and Technology, ShanghaiTech University, Shanghai (China)

    2015-03-01

    Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong to the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified.

  7. Genetic interaction network of the Saccharomyces cerevisiae type 1 phosphatase Glc7

    Directory of Open Access Journals (Sweden)

    Neszt Michael

    2008-07-01

    Full Text Available Abstract Background Protein kinases and phosphatases regulate protein phosphorylation, a critical means of modulating protein function, stability and localization. The identification of functional networks for protein phosphatases has been slow due to their redundant nature and the lack of large-scale analyses. We hypothesized that a genome-scale analysis of genetic interactions using the Synthetic Genetic Array could reveal protein phosphatase functional networks. We apply this approach to the conserved type 1 protein phosphatase Glc7, which regulates numerous cellular processes in budding yeast. Results We created a novel glc7 catalytic mutant (glc7-E101Q. Phenotypic analysis indicates that this novel allele exhibits slow growth and defects in glucose metabolism but normal cell cycle progression and chromosome segregation. This suggests that glc7-E101Q is a hypomorphic glc7 mutant. Synthetic Genetic Array analysis of glc7-E101Q revealed a broad network of 245 synthetic sick/lethal interactions reflecting that many processes are required when Glc7 function is compromised such as histone modification, chromosome segregation and cytokinesis, nutrient sensing and DNA damage. In addition, mitochondrial activity and inheritance and lipid metabolism were identified as new processes involved in buffering Glc7 function. An interaction network among 95 genes genetically interacting with GLC7 was constructed by integration of genetic and physical interaction data. The obtained network has a modular architecture, and the interconnection among the modules reflects the cooperation of the processes buffering Glc7 function. Conclusion We found 245 genes required for the normal growth of the glc7-E101Q mutant. Functional grouping of these genes and analysis of their physical and genetic interaction patterns bring new information on Glc7-regulated processes.

  8. Characterization of Schizophrenia Adverse Drug Interactions through a Network Approach and Drug Classification

    Directory of Open Access Journals (Sweden)

    Jingchun Sun

    2013-01-01

    Full Text Available Antipsychotic drugs are medications commonly for schizophrenia (SCZ treatment, which include two groups: typical and atypical. SCZ patients have multiple comorbidities, and the coadministration of drugs is quite common. This may result in adverse drug-drug interactions, which are events that occur when the effect of a drug is altered by the coadministration of another drug. Therefore, it is important to provide a comprehensive view of these interactions for further coadministration improvement. Here, we extracted SCZ drugs and their adverse drug interactions from the DrugBank and compiled a SCZ-specific adverse drug interaction network. This network included 28 SCZ drugs, 241 non-SCZs, and 991 interactions. By integrating the Anatomical Therapeutic Chemical (ATC classification with the network analysis, we characterized those interactions. Our results indicated that SCZ drugs tended to have more adverse drug interactions than other drugs. Furthermore, SCZ typical drugs had significant interactions with drugs of the “alimentary tract and metabolism” category while SCZ atypical drugs had significant interactions with drugs of the categories “nervous system” and “antiinfectives for systemic uses.” This study is the first to characterize the adverse drug interactions in the course of SCZ treatment and might provide useful information for the future SCZ treatment.

  9. Historical Determinants of Regional Divisions of Georgia and their Implications for Territorial Governance

    Directory of Open Access Journals (Sweden)

    Mądry Cezary

    2016-06-01

    Full Text Available Georgia can be characterised by its turbulent history, centuries-old traditions, and a great ethnic diversity. This makes it necessary to include historical determinants, in addition to geopolitical and economic factors, when making a regional analysis of its territory and contemporary governance issues. Five stages of the development of the present territorial division of Georgia are distinguished. They have been identified by means of an analysis of key events (critical junctures of significance in the formation of its historical regions. Additionally, their influence at each of the three levels of the current territorial division of independent Georgia is discussed, in particular in the context of territorial governance.

  10. Ibsen in Georgia: milestones in the reception

    Directory of Open Access Journals (Sweden)

    Kakhaber Loria

    2015-02-01

    Ibsen was and is constantly referred to in Georgian literary studies, not least in connection with Georgian writers. In post-Soviet Georgia, Ibsen is very much on the agenda, and his plays are produced and discussed as they always have been.

  11. Dollarization in emerging markets: evidence from Georgia

    Czech Academy of Sciences Publication Activity Database

    Loiseau-Aslanidi, Olga

    2012-01-01

    Roč. 48, č. 3 (2012), s. 70-84 ISSN 1540-496X Grant - others:UK(CZ) GAUK 259027 Institutional support: PRVOUK-P23 Keywords : dollarization * Georgia * money-in-utility function Subject RIV: AH - Economics Impact factor: 1.190, year: 2012

  12. Impedance-Based Harmonic Instability Assessment in Multiple Electric Trains and Traction Network Interaction System

    DEFF Research Database (Denmark)

    Tao, Haidong; Hu, Haitao; Wang, Xiongfei

    2018-01-01

    This paper presents an impedance-based method to systematically investigate the interaction between multi-train and traction networks, focusing on evaluating the harmonic instability problems. Firstly, the interaction mechanism of multi-train and the traction network is represented as a feedback ...

  13. Milkweed, stink bugs, and Georgia cotton

    Science.gov (United States)

    In peanut-cotton farmscapes in Georgia, stink bugs, i.e., Nezara viridula (L.)(Say) and Chinavia hilaris (Say), develop in peanut and then disperse at the crop-to-crop interface to feed on fruit in cotton. The main objective of this study was to examine the influence of a habitat of tropical milkwe...

  14. Oligomeric protein structure networks: insights into protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Brinda KV

    2005-12-01

    Full Text Available Abstract Background Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues. The analysis of such networks has been carried out in terms of amino acid clusters and hubs (highly connected residues with special emphasis to protein interfaces. Results A variety of interactions such as hydrogen bond, salt bridges, aromatic and hydrophobic interactions, which occur at the interfaces are identified in a consolidated manner as amino acid clusters at the interface, from this study. Moreover, the characterization of the highly connected hub-forming residues at the interfaces and their comparison with the hubs from the non-interface regions and the non-hubs in the interface regions show that there is a predominance of charged interactions at the interfaces. Further, strong and weak interfaces are identified on the basis of the interaction strength between amino acid residues and the sizes of the interface clusters, which also show that many protein interfaces are stronger than their monomeric protein cores. The interface strengths evaluated based on the interface clusters and hubs also correlate well with experimentally determined dissociation constants for known complexes. Finally, the interface hubs identified using the present method correlate very well with experimentally determined hotspots in the interfaces of protein complexes obtained from the Alanine Scanning Energetics database (ASEdb. A few predictions of interface hot

  15. Changes in Georgia restaurant and bar smoking policies from 2006 to 2012.

    Science.gov (United States)

    Chandora, Rachna D; Whitney, Carrie F; Weaver, Scott R; Eriksen, Michael P

    2015-05-14

    The purpose of this study is to examine the change in smoking policy status among Georgia restaurants and bars from 2006 to 2012 and to identify restaurant and bar characteristics that are associated with allowing smoking. Data were obtained from similar cross-sectional indoor air surveys conducted in 2006 and 2012 in Georgia. Both surveys were designed to gather information about restaurant and bar smoking policies. Weighted χ(2) analyses were performed to identify changes in smoking policy status and other variables from 2006 to 2012. Weighted logistic regression analysis was used to test for significant associations between an establishment's smoking policy and other characteristics. The percentage of restaurants and bars in Georgia that allowed smoking nearly doubled, from 9.1% in 2006 to 17.6% in 2012. The analyses also showed a significant increase in the percentage of establishments that allow smoking when minors are present. Having a liquor license was a significant predictor of allowing smoking. The Smokefree Air Act was enacted in 2005 to protect the health and welfare of Georgia citizens, but study results suggest that policy makers should reevaluate the law and consider strengthening it to make restaurants and bars 100% smokefree without exemptions.

  16. Impact of interaction style and degree on the evolution of cooperation on Barabási-Albert scale-free network.

    Directory of Open Access Journals (Sweden)

    Fengjie Xie

    Full Text Available In this work, we study an evolutionary prisoner's dilemma game (PDG on Barabási-Albert scale-free networks with limited player interactions, and explore the effect of interaction style and degree on cooperation. The results show that high-degree preference interaction, namely the most applicable interaction in the real world, is less beneficial for emergence of cooperation on scale-free networks than random interaction. Besides, cooperation on scale-free networks is enhanced with the increase of interaction degree regardless whether the interaction is high-degree preference or random. If the interaction degree is very low, the cooperation level on scale-free networks is much lower than that on regular ring networks, which is against the common belief that scale-free networks must be more beneficial for cooperation. Our analysis indicates that the interaction relations, the strategy and the game payoff of high-connectivity players play important roles in the evolution of cooperation on scale-free networks. A certain number of interactions are necessary for scale-free networks to exhibit strong capability of facilitating cooperation. Our work provides important insight for members on how to interact with others in a social organization.

  17. Different cell fates from cell-cell interactions: core architectures of two-cell bistable networks.

    Science.gov (United States)

    Rouault, Hervé; Hakim, Vincent

    2012-02-08

    The acquisition of different fates by cells that are initially in the same state is central to development. Here, we investigate the possible structures of bistable genetic networks that can allow two identical cells to acquire different fates through cell-cell interactions. Cell-autonomous bistable networks have been previously sampled using an evolutionary algorithm. We extend this evolutionary procedure to take into account interactions between cells. We obtain a variety of simple bistable networks that we classify into major subtypes. Some have long been proposed in the context of lateral inhibition through the Notch-Delta pathway, some have been more recently considered and others appear to be new and based on mechanisms not previously considered. The results highlight the role of posttranscriptional interactions and particularly of protein complexation and sequestration, which can replace cooperativity in transcriptional interactions. Some bistable networks are entirely based on posttranscriptional interactions and the simplest of these is found to lead, upon a single parameter change, to oscillations in the two cells with opposite phases. We provide qualitative explanations as well as mathematical analyses of the dynamical behaviors of various created networks. The results should help to identify and understand genetic structures implicated in cell-cell interactions and differentiation. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  18. 86th Annual Georgia Public Health Association Meeting & Conference Report.

    Science.gov (United States)

    Smith, Selina A; Abbott, Regina; Sims, Christy

    2015-01-01

    The 86 th annual meeting of the Georgia Public Health Association (GPHA) and joint conference with the Southern Health Association was held in Atlanta, Georgia, on April 13-14, 2015, with pre-conference (April 12 th ) and post-conference (April 14 th ) Executive Board meetings. As Georgia's leading forum for public health researchers, practitioners, and students, the annual meeting of the GPHA brings together participants from across the state to explore recent developments in the field and to exchange techniques, tools, and experiences. Historically, the GPHA conference has been held in Savannah (n=24); Jekyll Island (n=20); Atlanta (n=16); Augusta (n=4); and Gainesville (n=1). There was no annual meeting during the early years (1929-1936); during World War II (1941-1943 and 1945); and for four years during the 1980s. Between 2006 and 2010, GPHA held one-day annual meetings and business sessions with educational workshops. Several new initiatives were highlighted as part of this year's conference. These included a "move and groove" physical activity lounge, registration scholarships for students with a dedicated meet-and-greet reception, an expanded exhibit hall, presentation and approval of three resolutions (related to healthy foods at official activities and events; weapons at official activities and events; and memorials), and approval of the 2015 legislative policy positions and amended association bylaws. The theme for the conference was Advocacy in Action for Public Health . Specifically, the program addressed ensuring access to care; protecting funding for core programs, services, and infrastructure; eliminating health disparities; and addressing key public health issues important to the state of Georgia. One hundred and nine (109) abstracts were submitted for peer review; 36 were accepted for poster and 40 for workshop presentations. Four plenary sessions with keynote speakers covered the intersection between advocacy and policy, Georgia's response to the

  19. Network Interaction of Universities in Higher Education System of Ural Macro-Region

    Directory of Open Access Journals (Sweden)

    Garold Efimovich Zborovsky

    2017-06-01

    Full Text Available The subject-matter of the analysis are the characteristics and forms of cooperation between universities of Ural Federal District on the basis of their typology. The purpose of the article is to substantiate the necessity and possibility of network interaction between universities of the macro-region. We prove the importance and potential effectiveness of universities network interaction in the terms of socio-economic uncertainty of the development of Ural Federal District and its higher education. Networking interaction and multilateral cooperation are considered as a new type of inter-universities relations, which can be activated and intensified by strengthening the relations of universities with stakeholders. The authors examine certain concrete forms and formats of network interaction and cooperation between universities and discuss selected cases of new type of relations. In it, they see the real and potential innovation of higher school nonlinear development processes. The statements of the article allow to confirm the hypothesis about the reality of strengthening the network interaction in macro-region. It can transform higher education in the driver of socio-economic development of Ural Federal District; ensure the competitiveness of higher education of the macro-region in the Russian and global educational space; enhance its role in the society; become one of the most significant elements of nonlinear models of higher education development in the country. The authors’ research is based on the interdisciplinary methodology including the potential of theoretical sociology, sociology of higher education, economic sociology, management theory, regional economics. The results of the study can form the basis for the improvement of the Ural Federal District’s educational policy.

  20. Resiliency Programming for Adult Offenders in Georgia.

    Science.gov (United States)

    Rees, E. Frances

    2000-01-01

    Discusses resiliency programming as an alternative approach to program development for incarcerated adults, and describes a pilot project in a Georgia prison, Leadership Development, that uses the concept of resiliency to frame inmate education. Discusses implications of this model of correctional education. (SLD)

  1. Savannah, Georgia Tsunami Forecast Grids for MOST Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Savannah, Georgia Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

  2. Crucial role of strategy updating for coexistence of strategies in interaction networks

    Science.gov (United States)

    Zhang, Jianlei; Zhang, Chunyan; Cao, Ming; Weissing, Franz J.

    2015-04-01

    Network models are useful tools for studying the dynamics of social interactions in a structured population. After a round of interactions with the players in their local neighborhood, players update their strategy based on the comparison of their own payoff with the payoff of one of their neighbors. Here we show that the assumptions made on strategy updating are of crucial importance for the strategy dynamics. In the first step, we demonstrate that seemingly small deviations from the standard assumptions on updating have major implications for the evolutionary outcome of two cooperation games: cooperation can more easily persist in a Prisoner's Dilemma game, while it can go more easily extinct in a Snowdrift game. To explain these outcomes, we develop a general model for the updating of states in a network that allows us to derive conditions for the steady-state coexistence of states (or strategies). The analysis reveals that coexistence crucially depends on the number of agents consulted for updating. We conclude that updating rules are as important for evolution on a network as network structure and the nature of the interaction.

  3. Model-free inference of direct network interactions from nonlinear collective dynamics.

    Science.gov (United States)

    Casadiego, Jose; Nitzan, Mor; Hallerberg, Sarah; Timme, Marc

    2017-12-19

    The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.

  4. An attempt to understand glioma stem cell biology through centrality analysis of a protein interaction network.

    Science.gov (United States)

    Mallik, Mrinmay Kumar

    2018-02-07

    Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that

  5. Rainwater Harvesting and Social Networks: Visualising Interactions for Niche Governance, Resilience and Sustainability

    Directory of Open Access Journals (Sweden)

    Sarah Ward

    2016-11-01

    Full Text Available Visualising interactions across urban water systems to explore transition and change processes requires the development of methods and models at different scales. This paper contributes a model representing the network interactions of rainwater harvesting (RWH infrastructure innovators and other organisations in the UK RWH niche to identify how resilience and sustainability feature within niche governance in practice. The RWH network interaction model was constructed using a modified participatory social network analysis (SNA. The SNA was further analysed through the application of a two-part analytical framework based on niche management and the safe, resilient and sustainable (‘Safe and SuRe’ framework. Weak interactions between some RWH infrastructure innovators and other organisations highlighted reliance on a limited number of persuaders to influence the regime and landscape, which were underrepresented. Features from niche creation and management were exhibited by the RWH network interaction model, though some observed characteristics were not represented. Additional Safe and SuRe features were identified covering diverse innovation, responsivity, no protection, unconverged expectations, primary influencers, polycentric or adaptive governance and multiple learning-types. These features enable RWH infrastructure innovators and other organisations to reflect on improving resilience and sustainability, though further research in other sectors would be useful to verify and validate observation of the seven features.

  6. Metabolic network modeling of microbial interactions in natural and engineered environmental systems

    Directory of Open Access Journals (Sweden)

    Octavio ePerez-Garcia

    2016-05-01

    Full Text Available We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA, experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e. i lumped networks, ii compartment per guild networks, iii bi-level optimization simulations and iv dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial

  7. Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex

    Science.gov (United States)

    Hulsman, Marc; Lelieveldt, Boudewijn P. F.; de Ridder, Jeroen; Reinders, Marcel

    2015-01-01

    The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale). PMID:25965262

  8. Climate change vulnerability assessment in Georgia

    Science.gov (United States)

    Binita KC; J. Marshall Shepherd; Cassandra Johnson Gaither

    2015-01-01

    Climate change is occurring in the Southeastern United States, and one manifestation is changes in frequency and intensity of extreme events. A vulnerability assessment is performed in the state of Georgia (United States) at the county level from 1975 to 2012 in decadal increments. Climate change vulnerability is typically measured as a function of exposure to physical...

  9. Modeling human dynamics of face-to-face interaction networks

    OpenAIRE

    Starnini, Michele; Baronchelli, Andrea; Pastor-Satorras, Romualdo

    2013-01-01

    Face-to-face interaction networks describe social interactions in human gatherings, and are the substrate for processes such as epidemic spreading and gossip propagation. The bursty nature of human behavior characterizes many aspects of empirical data, such as the distribution of conversation lengths, of conversations per person, or of inter-conversation times. Despite several recent attempts, a general theoretical understanding of the global picture emerging from data is still lacking. Here ...

  10. Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model.

    Science.gov (United States)

    Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

    2016-10-06

    Comparative analysis of protein-protein interaction (PPI) networks provides an effective means of detecting conserved functional network modules across different species. Such modules typically consist of orthologous proteins with conserved interactions, which can be exploited to computationally predict the modules through network comparison. In this work, we propose a novel probabilistic framework for comparing PPI networks and effectively predicting the correspondence between proteins, represented as network nodes, that belong to conserved functional modules across the given PPI networks. The basic idea is to estimate the steady-state network flow between nodes that belong to different PPI networks based on a Markov random walk model. The random walker is designed to make random moves to adjacent nodes within a PPI network as well as cross-network moves between potential orthologous nodes with high sequence similarity. Based on this Markov random walk model, we estimate the steady-state network flow - or the long-term relative frequency of the transitions that the random walker makes - between nodes in different PPI networks, which can be used as a probabilistic score measuring their potential correspondence. Subsequently, the estimated scores can be used for detecting orthologous proteins in conserved functional modules through network alignment. Through evaluations based on multiple real PPI networks, we demonstrate that the proposed scheme leads to improved alignment results that are biologically more meaningful at reduced computational cost, outperforming the current state-of-the-art algorithms. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/CUFID .

  11. 78 FR 28118 - Vidalia Onions Grown in Georgia; Change in Reporting and Assessment Requirements

    Science.gov (United States)

    2013-05-14

    ... onion producers in the designated production area. Small agricultural service firms, which include...; FV13-955-1 IR] Vidalia Onions Grown in Georgia; Change in Reporting and Assessment Requirements AGENCY... Vidalia onions grown in Georgia (order). The order regulates the handling of Vidalia onions grown in...

  12. Health research capacity building in Georgia: a case-based needs assessment.

    Science.gov (United States)

    Squires, A; Chitashvili, T; Djibuti, M; Ridge, L; Chyun, D

    2017-06-01

    Research capacity building in the health sciences in low- and middle-income countries (LMICs) has typically focused on bench-science capacity, but research examining health service delivery and health workforce is equally necessary to determine the best ways to deliver care. The Republic of Georgia, formerly a part of the Soviet Union, has multiple issues within its healthcare system that would benefit from expended research capacity, but the current research environment needs to be explored prior to examining research-focused activities. The purpose of this project was to conduct a needs assessment focused on developing research capacity in the Republic of Georgia with an emphasis on workforce and network development. A case study approach guided by a needs assessment format. We conducted in-country, informal, semi-structured interviews in English with key informants and focus groups with faculty, students, and representatives of local non-governmental organizations. Purposive and snowball sampling approaches were used to recruit participants, with key informant interviews scheduled prior to arrival in country. Documents relevant to research capacity building were also included. Interview results were coded via content analysis. Final results were organized into a SWOT (strengths, weaknesses, opportunities, threat) analysis format, with the report shared with participants. There is widespread interest among students and faculty in Georgia around building research capacity. Lack of funding was identified by many informants as a barrier to research. Many critical research skills, such as proposal development, qualitative research skills, and statistical analysis, were reported as very limited. Participants expressed concerns about the ethics of research, with some suggesting that research is undertaken to punish or 'expose' subjects. However, students and faculty are highly motivated to improve their skills, are open to a variety of learning modalities, and have

  13. Simulating market dynamics: interactions between consumer psychology and social networks.

    Science.gov (United States)

    Janssen, Marco A; Jager, Wander

    2003-01-01

    Markets can show different types of dynamics, from quiet markets dominated by one or a few products, to markets with continual penetration of new and reintroduced products. In a previous article we explored the dynamics of markets from a psychological perspective using a multi-agent simulation model. The main results indicated that the behavioral rules dominating the artificial consumer's decision making determine the resulting market dynamics, such as fashions, lock-in, and unstable renewal. Results also show the importance of psychological variables like social networks, preferences, and the need for identity to explain the dynamics of markets. In this article we extend this work in two directions. First, we will focus on a more systematic investigation of the effects of different network structures. The previous article was based on Watts and Strogatz's approach, which describes the small-world and clustering characteristics in networks. More recent research demonstrated that many large networks display a scale-free power-law distribution for node connectivity. In terms of market dynamics this may imply that a small proportion of consumers may have an exceptional influence on the consumptive behavior of others (hubs, or early adapters). We show that market dynamics is a self-organized property depending on the interaction between the agents' decision-making process (heuristics), the product characteristics (degree of satisfaction of unit of consumption, visibility), and the structure of interactions between agents (size of network and hubs in a social network).

  14. A projection of motor fuel tax revenue and analysis of alternative revenue sources in Georgia.

    Science.gov (United States)

    2012-05-01

    Motor fuel tax revenue currently supplies the majority of funding for : transportation agencies at the state and federal level. Georgia uses excise and sales taxes : to generate revenue for the Georgia Department of Transportation (GDOT). Inflation a...

  15. Structural breakdown of specialized plant-herbivore interaction networks in tropical forest edges

    Directory of Open Access Journals (Sweden)

    Bruno Ximenes Pinho

    2017-10-01

    Full Text Available Plant-herbivore relationships are essential for ecosystem functioning, typically forming an ecological network with a compartmentalized (i.e. modular structure characterized by highly specialized interactions. Human disturbances can favor habitat generalist species and thus cause the collapse of this modular structure, but its effects are rarely assessed using a network-based approach. We investigate how edge proximity alters plant-insect herbivore networks by comparing forest edge and interior in a large remnant (3.500 ha of the Brazilian Atlantic forest. Given the typical dominance of pioneer plants and generalist herbivores in edge-affected habitats, we test the hypothesis that the specialized structure of plant-herbivore networks collapse in forest edges, resulting in lower modularity and herbivore specialization. Despite no differences in the number of species and interactions, the network structure presented marked differences between forest edges and interior. Herbivore specialization, modularity and number of modules were significantly higher in forest interior than edge-affected habitats. When compared to a random null model, two (22.2% and eight (88.8% networks were significantly modular in forest edge and interior, respectively. The loss of specificity and modularity in plant-herbivore networks in forest edges may be related to the loss of important functions, such as density-dependent control of superior plant competitors, which is ultimately responsible for the maintenance of biodiversity and ecosystem functions. Our results support previous warnings that focusing on traditional community measures only (e.g. species diversity may overlook important modifications in species interactions and ecosystem functioning.

  16. The association between sugar-sweetened beverages and dental caries among third-grade students in Georgia.

    Science.gov (United States)

    Wilder, Jocelyn R; Kaste, Linda M; Handler, Arden; Chapple-McGruder, Theresa; Rankin, Kristin M

    2016-01-01

    The purpose of this study is to examine the association between sugar-sweetened beverage (SSB) consumption and caries experience among Georgia third graders. The 2010-2011 Georgia Third Grade Oral Health Study provided a school-based sample for analysis. Data were weighted to be representative of the state of Georgia's third graders. Log-binomial regression was used to assess the association between SSB consumption and caries experience after adjusting for socio-demographic and maternal and child oral health characteristics. Georgia third graders consumed approximately two servings of SSB per day on average (1.7, 95% CI 1.6-1.8). Fifty-two percent of Georgia third graders had caries experience. Daily consumption of SSB and prevalence of caries experience differed significantly by demographic characteristics. After adjustment for socio-demographic and maternal oral health characteristics, caries experience increased 22 percent (adjusted PR = 1.2, 95% CI 1.1, 1.3) for every additional reported serving of SSB consumed per day. Higher consumption of SSBs is associated with higher caries prevalence among Georgia third graders after adjustment for important covariates. Consequently, health messages about SSBs from dentists, physicians, and other healthcare providers as well as policy approaches at the school, state, and national levels to limit consumption of SSBs may collectively impact both the development of dental caries and obesity, leading to overall better health for children. © 2015 American Association of Public Health Dentistry.

  17. Prediction of interface residue based on the features of residue interaction network.

    Science.gov (United States)

    Jiao, Xiong; Ranganathan, Shoba

    2017-11-07

    Protein-protein interaction plays a crucial role in the cellular biological processes. Interface prediction can improve our understanding of the molecular mechanisms of the related processes and functions. In this work, we propose a classification method to recognize the interface residue based on the features of a weighted residue interaction network. The random forest algorithm is used for the prediction and 16 network parameters and the B-factor are acting as the element of the input feature vector. Compared with other similar work, the method is feasible and effective. The relative importance of these features also be analyzed to identify the key feature for the prediction. Some biological meaning of the important feature is explained. The results of this work can be used for the related work about the structure-function relationship analysis via a residue interaction network model. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Protein function prediction using neighbor relativity in protein-protein interaction network.

    Science.gov (United States)

    Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

    2013-04-01

    There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

  19. Establishing Interaction between Machine and Medaka using Deep Q-Network

    Directory of Open Access Journals (Sweden)

    Ryo Nishimura

    2016-05-01

    Full Text Available Social interaction is the basic ability for animals to survive. It is difficult for a machine to interact with human or other animals because it is not clear how the machine should interact. This paper examines whether an artificial dot controlled by a machine can interact with a medaka and induce a desired behavior. The dot is displayed on a monitor. We use deep Q network (DQN to learn how to move the dot. As a result, the DQN could learn some basic elements to interact with the medaka and the desired behavior could be induced.

  20. Increased signaling entropy in cancer requires the scale-free property of protein interaction networks

    Science.gov (United States)

    Teschendorff, Andrew E.; Banerji, Christopher R. S.; Severini, Simone; Kuehn, Reimer; Sollich, Peter

    2015-01-01

    One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology. PMID:25919796

  1. Ground-water flow and water quality in the Upper Floridan aquifer, southwestern Albany area, Georgia, 1998-2001

    Science.gov (United States)

    Warner, Debbie; Lawrence, Stephen J.

    2005-01-01

    During 1997, the Dougherty County Health Department sampled more than 700 wells completed in the Upper Floridan aquifer in Dougherty County, Georgia, and determined that nitrate as nitrogen (hereinafter called nitrate) concentrations were above 10 milligrams per liter (mg/L) in 12 percent of the wells. Ten mg/L is the Georgia primary drinking-water standard. The ground-water flow system is complex and poorly understood in this predominantly agricultural area. Therefore, the U.S. Geological Survey (USGS) - in cooperation with Albany Water, Gas and Light Commission - conducted a study to better define ground-water flow and water quality in the Upper Florida aquifer in the southwestern Albany area, Georgia. Ground-water levels were measured in the southwestern Albany area, Georgia, during May 1998 and March 1999 (spring), and October 1998 and September 1999 (fall). Groundwater levels measured in 75 wells open only to the Upper Floridan aquifer were used to construct potentiometric-surface maps for those four time periods. These maps show that ground water generally flows from northwest to southeast at gradients ranging from about 2 to greater than 10 feet per mile. During spring and fall 1998, ground-water levels were high and mounding of the potentiometric surface occurred in the central part of the study area, indicating a local recharge area. Water levels declined from December through February, and by March 1999 the mound in the potentiometric surface had dissipated. Of the 75 wells in the potentiometric network, 24 were selected for a water-quality network. These 24 wells and 1 spring were sampled during fall 1998 and spring 1999. Samples were analyzed for major chemical constituents, selected minor constituents, selected nutrients, and chlorofluorocarbons (CFC). Water-quality field measurements - such as water temperature, pH, specific conductance (SC), and dissolved oxygen (DO) - were taken at each well. During August 2000, a ground-water sample was collected

  2. Individual and Group-Based Engagement in an Online Physical Activity Monitoring Program in Georgia.

    Science.gov (United States)

    Smith, Matthew Lee; Durrett, Nicholas K; Bowie, Maria; Berg, Alison; McCullick, Bryan A; LoPilato, Alexander C; Murray, Deborah

    2018-06-07

    Given the rising prevalence of obesity in the United States, innovative methods are needed to increase physical activity (PA) in community settings. Evidence suggests that individuals are more likely to engage in PA if they are given a choice of activities and have support from others (for encouragement, motivation, and accountability). The objective of this study was to describe the use of the online Walk Georgia PA tracking platform according to whether the user was an individual user or group user. Walk Georgia is a free, interactive online tracking platform that enables users to log PA by duration, activity, and perceived difficulty, and then converts these data into points based on metabolic equivalents. Users join individually or in groups and are encouraged to set weekly PA goals. Data were examined for 6,639 users (65.8% were group users) over 28 months. We used independent sample t tests and Mann-Whitney U tests to compare means between individual and group users. Two linear regression models were fitted to identify factors associated with activity logging. Users logged 218,766 activities (15,119,249 minutes of PA spanning 592,714 miles [41,858,446 points]). On average, group users had created accounts more recently than individual users (P < .001); however, group users logged more activities (P < .001). On average, group users logged more minutes of PA (P < .001) and earned more points (P < .001). Being in a group was associated with a larger proportion of weeks in which 150 minutes or more of weekly PA was logged (B = 20.47, P < .001). Use of Walk Georgia was significantly higher among group users than among individual users. To expand use and dissemination of online tracking of PA, programs should target naturally occurring groups (eg, workplaces, schools, faith-based groups).

  3. Exploitation of genetic interaction network topology for the prediction of epistatic behavior

    KAUST Repository

    Alanis Lobato, Gregorio

    2013-10-01

    Genetic interaction (GI) detection impacts the understanding of human disease and the ability to design personalized treatment. The mapping of every GI in most organisms is far from complete due to the combinatorial amount of gene deletions and knockdowns required. Computational techniques to predict new interactions based only on network topology have been developed in network science but never applied to GI networks.We show that topological prediction of GIs is possible with high precision and propose a graph dissimilarity index that is able to provide robust prediction in both dense and sparse networks.Computational prediction of GIs is a strong tool to aid high-throughput GI determination. The dissimilarity index we propose in this article is able to attain precise predictions that reduce the universe of candidate GIs to test in the lab. © 2013 Elsevier Inc.

  4. Exploitation of genetic interaction network topology for the prediction of epistatic behavior

    KAUST Repository

    Alanis Lobato, Gregorio; Cannistraci, Carlo; Ravasi, Timothy

    2013-01-01

    Genetic interaction (GI) detection impacts the understanding of human disease and the ability to design personalized treatment. The mapping of every GI in most organisms is far from complete due to the combinatorial amount of gene deletions and knockdowns required. Computational techniques to predict new interactions based only on network topology have been developed in network science but never applied to GI networks.We show that topological prediction of GIs is possible with high precision and propose a graph dissimilarity index that is able to provide robust prediction in both dense and sparse networks.Computational prediction of GIs is a strong tool to aid high-throughput GI determination. The dissimilarity index we propose in this article is able to attain precise predictions that reduce the universe of candidate GIs to test in the lab. © 2013 Elsevier Inc.

  5. Integrating Micro-level Interactions with Social Network Analysis in Tie Strength Research

    DEFF Research Database (Denmark)

    Torre, Osku; Gupta, Jayesh Prakash; Kärkkäinen, Hannu

    2017-01-01

    of tie strength based on reciprocal interaction from publicly available Facebook data, and suggest that this approach could work as a basis for further tie strength studies. Our approach makes use of weak tie theory, and enables researchers to study micro-level interactions (i.e. discussions, messages......A social tie is a target for ongoing, high-level scientific debate. Measuring the tie strength in social networks has been an important topic for academic studies since Mark Granovetter's seminal papers in 1970's. However, it is still a problematic issue mainly for two reasons: 1) existing tie...... strengthening process in online social networks. Therefore, we suggest a new approach to tie strength research, which focuses on studying communication patterns (edges) more rather than actors (nodes) in a social network. In this paper we build a social network analysis-based approach to enable the evaluation...

  6. STEM Career Cluster Engineering and Technology Education pathway in Georgia: Perceptions of Georgia engineering and technology education high school teachers and CTAE administrators as measured by the Characteristics of Engineering and Technology Education survey

    Science.gov (United States)

    Crenshaw, Mark VanBuren

    This study examined the perceptions held by Georgia Science, Technology, Engineering, and Mathematics (STEM) Career Cluster Engineering and Technology Education (ETE) high school pathway teachers and Georgia's Career, Technical and Agriculture Education (CTAE) administrators regarding the ETE pathway and its effect on implementation within their district and schools. It provides strategies for ETE teaching methods, curriculum content, STEM integration, and how to improve the ETE pathway program of study. Current teaching and curricular trends were examined in ETE as well as the role ETE should play as related to STEM education. The study, using the Characteristics of Engineering and Technology Education Survey, was conducted to answer the following research questions: (a) Is there a significant difference in the perception of ETE teaching methodology between Georgia ETE high school teachers and CTAE administrators as measured by the Characteristics of Engineering and Technology Education Survey? (b) Is there a significant difference in the perception of ETE curriculum content between Georgia ETE high school teachers and CTAE administrators as measured by the Characteristics of Engineering and Technology Education Survey? (c) Is there a significant difference in the perception of STEM integration in the ETE high school pathway between Georgia ETE high school teachers and CTAE administrators as measured by the Characteristics of Engineering and Technology Education Survey? and (d) Is there a significant difference in the perception of how to improve the ETE high school pathway between Georgia ETE high school teachers and CTAE administrators as measured by the Characteristics of Engineering and Technology Education Survey? Suggestions for further research also were offered.

  7. Modeling and Detecting Feature Interactions among Integrated Services of Home Network Systems

    Science.gov (United States)

    Igaki, Hiroshi; Nakamura, Masahide

    This paper presents a framework for formalizing and detecting feature interactions (FIs) in the emerging smart home domain. We first establish a model of home network system (HNS), where every networked appliance (or the HNS environment) is characterized as an object consisting of properties and methods. Then, every HNS service is defined as a sequence of method invocations of the appliances. Within the model, we next formalize two kinds of FIs: (a) appliance interactions and (b) environment interactions. An appliance interaction occurs when two method invocations conflict on the same appliance, whereas an environment interaction arises when two method invocations conflict indirectly via the environment. Finally, we propose offline and online methods that detect FIs before service deployment and during execution, respectively. Through a case study with seven practical services, it is shown that the proposed framework is generic enough to capture feature interactions in HNS integrated services. We also discuss several FI resolution schemes within the proposed framework.

  8. Feed forward neural networks modeling for K-P interactions

    International Nuclear Information System (INIS)

    El-Bakry, M.Y.

    2003-01-01

    Artificial intelligence techniques involving neural networks became vital modeling tools where model dynamics are difficult to track with conventional techniques. The paper make use of the feed forward neural networks (FFNN) to model the charged multiplicity distribution of K-P interactions at high energies. The FFNN was trained using experimental data for the multiplicity distributions at different lab momenta. Results of the FFNN model were compared to that generated using the parton two fireball model and the experimental data. The proposed FFNN model results showed good fitting to the experimental data. The neural network model performance was also tested at non-trained space and was found to be in good agreement with the experimental data

  9. The management of interaction networks. The ???in-between??? concept within social work and counseling

    OpenAIRE

    Hern??ndez-Aristu, Jes??s

    2015-01-01

    We are familiar with the field of group interaction through the traditional work of Kurt Lewin and also systemic thinking talks about network interaction that builds up the system. Martin Buber also discusses the ???in-between??? concept as the third element.The therapist or counselor, social worker and clients are part of an interaction network, representing therapeutic and social working situations. Success in treatment and reflective processes, depends on the perception and managemen...

  10. The RING 2.0 web server for high quality residue interaction networks.

    Science.gov (United States)

    Piovesan, Damiano; Minervini, Giovanni; Tosatto, Silvio C E

    2016-07-08

    Residue interaction networks (RINs) are an alternative way of representing protein structures where nodes are residues and arcs physico-chemical interactions. RINs have been extensively and successfully used for analysing mutation effects, protein folding, domain-domain communication and catalytic activity. Here we present RING 2.0, a new version of the RING software for the identification of covalent and non-covalent bonds in protein structures, including π-π stacking and π-cation interactions. RING 2.0 is extremely fast and generates both intra and inter-chain interactions including solvent and ligand atoms. The generated networks are very accurate and reliable thanks to a complex empirical re-parameterization of distance thresholds performed on the entire Protein Data Bank. By default, RING output is generated with optimal parameters but the web server provides an exhaustive interface to customize the calculation. The network can be visualized directly in the browser or in Cytoscape. Alternatively, the RING-Viz script for Pymol allows visualizing the interactions at atomic level in the structure. The web server and RING-Viz, together with an extensive help and tutorial, are available from URL: http://protein.bio.unipd.it/ring. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  11. Depressive Symptoms and Their Interactions With Emotions and Personality Traits Over Time: Interaction Networks in a Psychiatric Clinic.

    Science.gov (United States)

    Semino, Laura N; Marksteiner, Josef; Brauchle, Gernot; Danay, Erik

    2017-04-13

    Associations between depression, personality traits, and emotions are complex and reciprocal. The aim of this study is to explore these interactions in dynamical networks and in a linear way over time depending on the severity of depression. Participants included 110 patients with depressive symptoms (DSM-5 criteria) who were recruited between October 2015 and February 2016 during their inpatient stay in a general psychiatric hospital in Hall in Tyrol, Austria. The patients filled out the Beck Depression Inventory-II, a German emotional competence questionnaire (Emotionale Kompetenz Fragebogen), Positive and Negative Affect Schedule, and the German versions of the Big Five Inventory-short form and State-Trait-Anxiety-Depression Inventory regarding symptoms, emotions, and personality during their inpatient stay and at a 3-month follow-up by mail. Network and regression analyses were performed to explore interactions both in a linear and a dynamical way at baseline and 3 months later. Regression analyses showed that emotions and personality traits gain importance for the prediction of depressive symptoms with decreasing symptomatology at follow-up (personality: baseline, adjusted R2 = 0.24, P personality traits is significantly denser and more interconnected (network comparison test: P = .03) at follow-up than at baseline, meaning that with decreased symptoms interconnections get stronger. During depression, personality traits and emotions are walled off and not strongly interconnected with depressive symptoms in networks. With decreasing depressive symptomatology, interfusing of these areas begins and interconnections become stronger. This finding has practical implications for interventions in an acute depressive state and with decreased symptoms. The network approach offers a new perspective on interactions and is a way to make the complexity of these interactions more tangible. © Copyright 2017 Physicians Postgraduate Press, Inc.

  12. Georgia Compliance Review Self-Study FY 01.

    Science.gov (United States)

    Georgia State Dept. of Education, Atlanta.

    Intended for evaluation of local compliance with special education federal and state legal requirements, this compliance review document includes both the compliance requirements and the criteria by which compliance is determined during the onsite compliance review of Georgia local school systems and state-operated programs. Each legal requirement…

  13. Social Networking Sites as Communication, Interaction, and Learning Environments: Perceptions and Preferences of Distance Education Students

    Science.gov (United States)

    Bozkurt, Aras; Karadeniz, Abdulkadir; Kocdar, Serpil

    2017-01-01

    The advent of Web 2.0 technologies transformed online networks into interactive spaces in which user-generated content has become the core material. With the possibilities that emerged from Web 2.0, social networking sites became very popular. The capability of social networking sites promises opportunities for communication and interaction,…

  14. Social network analysis as a method for analyzing interaction in collaborative online learning environments

    Directory of Open Access Journals (Sweden)

    Patricia Rice Doran

    2011-12-01

    Full Text Available Social network analysis software such as NodeXL has been used to describe participation and interaction in numerous social networks, but it has not yet been widely used to examine dynamics in online classes, where participation is frequently required rather than optional and participation patterns may be impacted by the requirements of the class, the instructor’s activities, or participants’ intrinsic engagement with the subject matter. Such social network analysis, which examines the dynamics and interactions among groups of participants in a social network or learning group, can be valuable in programs focused on teaching collaborative and communicative skills, including teacher preparation programs. Applied to these programs, social network analysis can provide information about instructional practices likely to facilitate student interaction and collaboration across diverse student populations. This exploratory study used NodeXL to visualize students’ participation in an online course, with the goal of identifying (1 ways in which NodeXL could be used to describe patterns in participant interaction within an instructional setting and (2 identifying specific patterns in participant interaction among students in this particular course. In this sample, general education teachers demonstrated higher measures of connection and interaction with other participants than did those from specialist (ESOL or special education backgrounds, and tended to interact more frequently with all participants than the majority of participants from specialist backgrounds. We recommend further research to delineate specific applications of NodeXL within an instructional context, particularly to identify potential patterns in student participation based on variables such as gender, background, cultural and linguistic heritage, prior training and education, and prior experience so that instructors can ensure their practice helps to facilitate student interaction

  15. Emergence of structural patterns out of synchronization in networks with competitive interactions

    Science.gov (United States)

    Assenza, Salvatore; Gutiérrez, Ricardo; Gómez-Gardeñes, Jesús; Latora, Vito; Boccaletti, Stefano

    2011-09-01

    Synchronization is a collective phenomenon occurring in systems of interacting units, and is ubiquitous in nature, society and technology. Recent studies have enlightened the important role played by the interaction topology on the emergence of synchronized states. However, most of these studies neglect that real world systems change their interaction patterns in time. Here, we analyze synchronization features in networks in which structural and dynamical features co-evolve. The feedback of the node dynamics on the interaction pattern is ruled by the competition of two mechanisms: homophily (reinforcing those interactions with other correlated units in the graph) and homeostasis (preserving the value of the input strength received by each unit). The competition between these two adaptive principles leads to the emergence of key structural properties observed in real world networks, such as modular and scale-free structures, together with a striking enhancement of local synchronization in systems with no global order.

  16. Exact tensor network ansatz for strongly interacting systems

    Science.gov (United States)

    Zaletel, Michael P.

    It appears that the tensor network ansatz, while not quite complete, is an efficient coordinate system for the tiny subset of a many-body Hilbert space which can be realized as a low energy state of a local Hamiltonian. However, we don't fully understand precisely which phases are captured by the tensor network ansatz, how to compute their physical observables (even numerically), or how to compute a tensor network representation for a ground state given a microscopic Hamiltonian. These questions are algorithmic in nature, but their resolution is intimately related to understanding the nature of quantum entanglement in many-body systems. For this reason it is useful to compute the tensor network representation of various `model' wavefunctions representative of different phases of matter; this allows us to understand how the entanglement properties of each phase are expressed in the tensor network ansatz, and can serve as test cases for algorithm development. Condensed matter physics has many illuminating model wavefunctions, such as Laughlin's celebrated wave function for the fractional quantum Hall effect, the Bardeen-Cooper-Schrieffer wave function for superconductivity, and Anderson's resonating valence bond ansatz for spin liquids. This thesis presents some results on exact tensor network representations of these model wavefunctions. In addition, a tensor network representation is given for the time evolution operator of a long-range one-dimensional Hamiltonian, which allows one to numerically simulate the time evolution of power-law interacting spin chains as well as two-dimensional strips and cylinders.

  17. Oral Histories of Nurse-Midwives in Georgia, 1970-1989: Blazing Trails, Building Fences, Raising Towers.

    Science.gov (United States)

    Thrower, Eileen J B

    2018-05-26

    This article provides an account of the establishment and development of the contemporary nurse-midwifery profession in Georgia, which was previously undocumented. Oral history interviews with nurse-midwives who were in clinical and educational practice in Georgia during the 1970s and 1980s were collected and analyzed to identify factors that affected the establishment of nurse-midwifery in this state. This study relied on historical methodology. Oral history interviews provided primary sources for analysis. Secondary sources included archives belonging to the narrators' nurse-midwifery services as well as scholarly and professional publications from 1923 to the present. Data were analyzed using Miller-Rosser and colleagues' method. In-depth interviews were conducted with 14 nurse-midwives who worked in clinical practice or education in Georgia in the 1970s and 1980s. The narrators' testimonies revealed facilitators for the establishment of nurse-midwifery in Georgia, including increasing access to care, providing woman-centered care, interprofessional relationships, and the support of peers. Resistance from the medical profession, financial constraints, and public misconceptions were identified as barriers for the profession. Oral histories in this study provided insight into the experiences of nurse-midwives in Georgia as they practiced and taught in the 1970s and 1980s. Interprofessional connections and cooperation supported the nurse-midwifery profession, and relationships with peers anchored the nurse-midwives. Mentoring relationships and interprofessional collaboration supported the nurse-midwives as they adapted and evolved to meet the needs of women in Georgia. © 2018 by the American College of Nurse-Midwives.

  18. A Bipartite Network-based Method for Prediction of Long Non-coding RNA–protein Interactions

    Directory of Open Access Journals (Sweden)

    Mengqu Ge

    2016-02-01

    Full Text Available As one large class of non-coding RNAs (ncRNAs, long ncRNAs (lncRNAs have gained considerable attention in recent years. Mutations and dysfunction of lncRNAs have been implicated in human disorders. Many lncRNAs exert their effects through interactions with the corresponding RNA-binding proteins. Several computational approaches have been developed, but only few are able to perform the prediction of these interactions from a network-based point of view. Here, we introduce a computational method named lncRNA–protein bipartite network inference (LPBNI. LPBNI aims to identify potential lncRNA–interacting proteins, by making full use of the known lncRNA–protein interactions. Leave-one-out cross validation (LOOCV test shows that LPBNI significantly outperforms other network-based methods, including random walk (RWR and protein-based collaborative filtering (ProCF. Furthermore, a case study was performed to demonstrate the performance of LPBNI using real data in predicting potential lncRNA–interacting proteins.

  19. Educational Initiatives for Industrial Development in Georgia.

    Science.gov (United States)

    Starnes, Paul M.; Johnson, Berman E.

    Georgia's two-year technical institutes have played a prominant role in linking education with industry. Five major interrelated efforts have worked to transform the state from an agrarian economy to one utilizing advanced technologies. The first of these, the Quick-Start Program, offers state-paid services, such as consultation, employee…

  20. Monitoring of Students' Interaction in Online Learning Settings by Structural Network Analysis and Indicators.

    Science.gov (United States)

    Ammenwerth, Elske; Hackl, Werner O

    2017-01-01

    Learning as a constructive process works best in interaction with other learners. Support of social interaction processes is a particular challenge within online learning settings due to the spatial and temporal distribution of participants. It should thus be carefully monitored. We present structural network analysis and related indicators to analyse and visualize interaction patterns of participants in online learning settings. We validate this approach in two online courses and show how the visualization helps to monitor interaction and to identify activity profiles of learners. Structural network analysis is a feasible approach for an analysis of the intensity and direction of interaction in online learning settings.

  1. A Preliminary Examination of the Relationship Between Social Networking Interactions, Internet Use, and Thwarted Belongingness.

    Science.gov (United States)

    Moberg, Fallon B; Anestis, Michael D

    2015-01-01

    Joiner's (2005) interpersonal-psychological theory of suicide hypothesizes that suicidal desire develops in response to the joint presence of thwarted belongingness and perceived burdensomeness. To consider the potential influence of online interactions and behaviors on these outcomes. To address this, we administered an online protocol assessing suicidal desire and online interactions in a sample of 305 undergraduates (83.6% female). We hypothesized negative interactions on social networking sites and a preference for online social interactions would be associated with thwarted belongingness. We also conducted an exploratory analysis examining the associations between Internet usage and perceived burdensomeness. Higher levels of negative interactions on social networking sites, but no other variables, significantly predicted thwarted belongingness. Our exploratory analysis showed that none of our predictors were associated with perceived burdensomeness after accounting for demographics, depression, and thwarted belongingness. Our findings indicate that a general tendency to have negative interactions on social networking sites could possibly impact suicidal desire and that these effects are significant above and beyond depression symptoms. Furthermore, no other aspect of problematic Internet use significantly predicted our outcomes in multivariate analyses, indicating that social networking in particular may have a robust effect on thwarted belongingness.

  2. HPIminer: A text mining system for building and visualizing human protein interaction networks and pathways.

    Science.gov (United States)

    Subramani, Suresh; Kalpana, Raja; Monickaraj, Pankaj Moses; Natarajan, Jeyakumar

    2015-04-01

    The knowledge on protein-protein interactions (PPI) and their related pathways are equally important to understand the biological functions of the living cell. Such information on human proteins is highly desirable to understand the mechanism of several diseases such as cancer, diabetes, and Alzheimer's disease. Because much of that information is buried in biomedical literature, an automated text mining system for visualizing human PPI and pathways is highly desirable. In this paper, we present HPIminer, a text mining system for visualizing human protein interactions and pathways from biomedical literature. HPIminer extracts human PPI information and PPI pairs from biomedical literature, and visualize their associated interactions, networks and pathways using two curated databases HPRD and KEGG. To our knowledge, HPIminer is the first system to build interaction networks from literature as well as curated databases. Further, the new interactions mined only from literature and not reported earlier in databases are highlighted as new. A comparative study with other similar tools shows that the resultant network is more informative and provides additional information on interacting proteins and their associated networks. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Fire blight in Georgia

    Directory of Open Access Journals (Sweden)

    Dali L. Gaganidze

    2018-03-01

    Full Text Available Fire blight is distinguished among the fruit tree diseases by harmfulness. Fire blight damages about 180 cultural and wild plants belonging to the Rosaceae family. Quince, apple and pear are the most susceptible to the disease. At present, the disease occurs in over 40 countries of Europe and Asia. Economic damage caused by fire blight is expressed not only in crop losses, but also, it poses threat of eradication to entire fruit tree gardens. Erwinia amylovora, causative bacteria of fire blight in fruit trees, is included in the A2 list of quarantine organisms. In 2016, the employees of the Plant Pest Diagnostic Department of the Laboratory of the Georgian Ministry of Agriculture have detected Erwinia amylovora in apple seedlings from Mtskheta district. National Food Agency, Ministry of Agriculture of Georgia informed FAO on pathogen detection. The aim of the study is detection of the bacterium Erwinia amylovora by molecular method (PCR in the samples of fruit trees, suspicious on fire blight collected in the regions of Eastern (Kvemo Kartli, Shida Kartli and Kakheti and Western Georgia (Imereti.The bacterium Erwinia amylovora was detected by real time and conventional PCR methods using specific primers and thus the fire blight disease confirmed in 23 samples of plant material from Shida Kartli (11 apples, 6 pear and 6 quince samples, in 5 samples from Kvemo Kartli (1 quince and 4 apple samples, in 2 samples of apples from Kakheti region and 1 sample of pear collected in Imereti (Zestafoni. Keywords: Fire blight, Erwinia amylovora, Conventional PCR, Real time PCR, DNA, Bacterium

  4. Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks

    Directory of Open Access Journals (Sweden)

    Kirouac Daniel C

    2012-05-01

    Full Text Available Abstract Background Understanding the information-processing capabilities of signal transduction networks, how those networks are disrupted in disease, and rationally designing therapies to manipulate diseased states require systematic and accurate reconstruction of network topology. Data on networks central to human physiology, such as the inflammatory signalling networks analyzed here, are found in a multiplicity of on-line resources of pathway and interactome databases (Cancer CellMap, GeneGo, KEGG, NCI-Pathway Interactome Database (NCI-PID, PANTHER, Reactome, I2D, and STRING. We sought to determine whether these databases contain overlapping information and whether they can be used to construct high reliability prior knowledge networks for subsequent modeling of experimental data. Results We have assembled an ensemble network from multiple on-line sources representing a significant portion of all machine-readable and reconcilable human knowledge on proteins and protein interactions involved in inflammation. This ensemble network has many features expected of complex signalling networks assembled from high-throughput data: a power law distribution of both node degree and edge annotations, and topological features of a “bow tie” architecture in which diverse pathways converge on a highly conserved set of enzymatic cascades focused around PI3K/AKT, MAPK/ERK, JAK/STAT, NFκB, and apoptotic signaling. Individual pathways exhibit “fuzzy” modularity that is statistically significant but still involving a majority of “cross-talk” interactions. However, we find that the most widely used pathway databases are highly inconsistent with respect to the actual constituents and interactions in this network. Using a set of growth factor signalling networks as examples (epidermal growth factor, transforming growth factor-beta, tumor necrosis factor, and wingless, we find a multiplicity of network topologies in which receptors couple to downstream

  5. Networks and Interactivity

    DEFF Research Database (Denmark)

    Considine, Mark; Lewis, Jenny

    2012-01-01

    of `street-level' employment services staff for the impacts of this. Contrary to expectations, networking has generally declined over the last decade. There are signs of path dependence in networking patterns within each country, but also a convergence of patterns for the UK and Australia......The systemic reform of employment services in OECD countries was driven by New Public Management (NPM) and then post-NPM reforms, when first-phase changes such as privatization were amended with `joined up' processes to help manage fragmentation. This article examines the networking strategies......, but not The Netherlands. Networking appears to be mediated by policy and regulatory imperatives....

  6. Study of Personalized Network Tutoring System Based on Emotional-cognitive Interaction

    Science.gov (United States)

    Qi, Manfei; Ma, Ding; Wang, Wansen

    Aiming at emotion deficiency in present Network tutoring system, a lot of negative effects is analyzed and corresponding countermeasures are proposed. The model of Personalized Network tutoring system based on Emotional-cognitive interaction is constructed in the paper. The key techniques of realizing the system such as constructing emotional model and adjusting teaching strategies are also introduced.

  7. 75 FR 61959 - Georgia-Alabama-South Carolina System

    Science.gov (United States)

    2010-10-06

    ... applicable to Southeastern power sold to existing preference customers in Mississippi, Florida, Georgia... FURTHER INFORMATION CONTACT: Leon Jourolmon, Assistant Administrator, Finance and Marketing, Southeastern... With the current proposed rate increase, customers will need to evaluate whether or not to continue to...

  8. Learning Predictive Interactions Using Information Gain and Bayesian Network Scoring.

    Directory of Open Access Journals (Sweden)

    Xia Jiang

    Full Text Available The problems of correlation and classification are long-standing in the fields of statistics and machine learning, and techniques have been developed to address these problems. We are now in the era of high-dimensional data, which is data that can concern billions of variables. These data present new challenges. In particular, it is difficult to discover predictive variables, when each variable has little marginal effect. An example concerns Genome-wide Association Studies (GWAS datasets, which involve millions of single nucleotide polymorphism (SNPs, where some of the SNPs interact epistatically to affect disease status. Towards determining these interacting SNPs, researchers developed techniques that addressed this specific problem. However, the problem is more general, and so these techniques are applicable to other problems concerning interactions. A difficulty with many of these techniques is that they do not distinguish whether a learned interaction is actually an interaction or whether it involves several variables with strong marginal effects.We address this problem using information gain and Bayesian network scoring. First, we identify candidate interactions by determining whether together variables provide more information than they do separately. Then we use Bayesian network scoring to see if a candidate interaction really is a likely model. Our strategy is called MBS-IGain. Using 100 simulated datasets and a real GWAS Alzheimer's dataset, we investigated the performance of MBS-IGain.When analyzing the simulated datasets, MBS-IGain substantially out-performed nine previous methods at locating interacting predictors, and at identifying interactions exactly. When analyzing the real Alzheimer's dataset, we obtained new results and results that substantiated previous findings. We conclude that MBS-IGain is highly effective at finding interactions in high-dimensional datasets. This result is significant because we have increasingly

  9. Repulsive interactions between two polyelectrolyte networks

    Science.gov (United States)

    Erbas, Aykut; Olvera de La Cruz, Monica; Olvera Group Collaboration

    Surfaces formed by charged polymeric species are highly_abundant in both synthetic and biological systems, for which maintaining_an optimum contact distance and a pressure balance is paramount. We investigate interactions between surfaces of two same-charged and_highly swollen polyelectrolyte gels, using extensive molecular dynamic_simulations and minimal analytical methods. The external-pressure_responses of the gels and the polymer-free ionic solvent layer separating_two surfaces are considered. Simulations confirmed that the surfaces are_held apart by osmotic pressure resulting from excess charges diffusing out_of the network. Both the solvent layer and pressure dependence are well_described by an analytical model based on the Poisson -Boltzmann solution for low and moderate electrostatic strengths. Our results can be of great importance for systems where charged gels or gel-like structures interact in various solvents, including systems encapsulated by gels and microgels in confinement.

  10. Modeling of intracerebral interictal epileptic discharges: Evidence for network interactions.

    Science.gov (United States)

    Meesters, Stephan; Ossenblok, Pauly; Colon, Albert; Wagner, Louis; Schijns, Olaf; Boon, Paul; Florack, Luc; Fuster, Andrea

    2018-06-01

    The interictal epileptic discharges (IEDs) occurring in stereotactic EEG (SEEG) recordings are in general abundant compared to ictal discharges, but difficult to interpret due to complex underlying network interactions. A framework is developed to model these network interactions. To identify the synchronized neuronal activity underlying the IEDs, the variation in correlation over time of the SEEG signals is related to the occurrence of IEDs using the general linear model. The interdependency is assessed of the brain areas that reflect highly synchronized neural activity by applying independent component analysis, followed by cluster analysis of the spatial distributions of the independent components. The spatiotemporal interactions of the spike clusters reveal the leading or lagging of brain areas. The analysis framework was evaluated for five successfully operated patients, showing that the spike cluster that was related to the MRI-visible brain lesions coincided with the seizure onset zone. The additional value of the framework was demonstrated for two more patients, who were MRI-negative and for whom surgery was not successful. A network approach is promising in case of complex epilepsies. Analysis of IEDs is considered a valuable addition to routine review of SEEG recordings, with the potential to increase the success rate of epilepsy surgery. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  11. Radiation sources and materials safety and security in Georgia

    International Nuclear Information System (INIS)

    Mandjgaladze, G.; Tsitskishvili, M.; Abramidze, Sh.; Katamadze, N.

    1998-01-01

    This paper explains the problems of safety and security in Georgia, the most important incidents and accidents, their consequences (including severe injuries and deaths) and governmental actions for prevention and mitigation. (author)

  12. Robust Weak Chimeras in Oscillator Networks with Delayed Linear and Quadratic Interactions

    Science.gov (United States)

    Bick, Christian; Sebek, Michael; Kiss, István Z.

    2017-10-01

    We present an approach to generate chimera dynamics (localized frequency synchrony) in oscillator networks with two populations of (at least) two elements using a general method based on a delayed interaction with linear and quadratic terms. The coupling design yields robust chimeras through a phase-model-based design of the delay and the ratio of linear and quadratic components of the interactions. We demonstrate the method in the Brusselator model and experiments with electrochemical oscillators. The technique opens the way to directly bridge chimera dynamics in phase models and real-world oscillator networks.

  13. Designing effective power sector reform: A road map for the republic of Georgia

    Science.gov (United States)

    Kurdgelashvili, Lado

    Around the world, network utilities (i.e., electricity, natural gas, railway, telecommunications, and water supply industries) are undergoing major structural transformation. A new wave of market liberalization, together with rapid technological changes, has challenged the previously dominant monopoly organization of these industries. A global trend toward deregulation and restructuring is evident in countries at different levels of social and economic development. The challenges of transition from a monopolistic to an open market competitive structure are numerous. Understanding these problems and finding solutions are essential to successful restructuring. In developing countries and economies in transition (i.e., the Eastern Europe and the former Soviet Union), government-owned utilities are often considered to be highly inefficient. The dominant power sector restructuring strategies seek to promote economic efficiency through a gradual introduction of competition into the power sector. Five components of power sector reform are commonly proposed by the World Bank and others for these countries: commercialization, privatization, establishment of an independent regulatory agency, unbundling and gradual introduction of competition in generation and retail markets. The Republic of Georgia, like many economies in transition (e.g., Hungary, Ukraine, and Kazakhstan) has followed this reform model. However, outcomes of the reform have not been as promised. The acute economic problems facing Georgia after it regained independence have compounded problems in the power sector. A review of Georgia's utility reforms reveals that the country has undertaken electricity industry restructuring without giving substantial consideration to the problems that these reforms might have created within the industry or society. The main task of this dissertation is to find the restructuring model, which can best serve economic, social and environmental goals under circumstances similar

  14. Primary headache disorders in the Republic of Georgia: prevalence and risk factors

    DEFF Research Database (Denmark)

    Katsarava, Z; Dzagnidze, A; Kukava, M

    2009-01-01

    OBJECTIVE: To estimate the 1-year prevalences of migraine and tension-type headache (TTH), and identify their principal risk factors, in the general population of the Republic of Georgia. METHODS: In a community-based door-to-door survey, 4 medical residents interviewed all biologically unrelated......, a remarkably high percentage of the population of Georgia have headache on >/=15 days/month. This study demonstrates the importance of socioeconomic factors in a developing country and unmasks the unmet needs of people with headache disorders....

  15. Determinants and consequences of health worker motivation in hospitals in Jordan and Georgia.

    Science.gov (United States)

    Franco, Lynne Miller; Bennett, Sara; Kanfer, Ruth; Stubblebine, Patrick

    2004-01-01

    Health worker motivation reflects the interactions between workers and their work environment. Because of the interactive nature of motivation, local organizational and broader sector policies have the potential to affect motivation of health workers, either positively or negatively, and as such to influence health system performance. Yet little is known about the key determinants and outcomes of motivation in developing and transition countries. This exploratory research, unique in its broader study of a whole range of motivational determinants and outcomes, was conducted in two hospitals in Jordan and two in Georgia. Three complementary approaches to data collection were used: (1) a contextual analysis; (2) a qualitative 360-degree assessment; and (3) a quantitative in-depth analysis focused on the individual determinants and outcomes of the worker's motivational process. A wide range of psychometric scales was used to assess personality differences, perceived contextual factors and motivational outcomes (feelings, thoughts and behaviors) on close to 500 employees in each country. Although Jordan and Georgia have very different cultural and socio-economic environments, the results from these two countries exhibited many similarities among key determinants: self-efficacy, pride, management openness, job properties, and values had significant effects on motivational outcomes in both countries. Where results were divergent, differences between the two countries highlight the importance of local culture on motivational issues, and the need to tailor motivational interventions to the specific issues related to particular professional or other groupings in the workforce. While workers themselves state that financial reward is critical for their work satisfaction, the data suggest a number of non-financial interventions that may be more effective means to improve worker motivation. This research highlights the complexity of worker motivation, and the need for a more

  16. Network of interactions between ciliates and phytoplankton during spring

    Directory of Open Access Journals (Sweden)

    Thomas ePosch

    2015-11-01

    Full Text Available The annually recurrent spring phytoplankton blooms in freshwater lakes initiate pronounced successions of planktonic ciliate species. Although there is considerable knowledge on the taxonomic diversity of these ciliates, their species-specific interactions with other microorganisms are still not well understood. Here we present the succession patterns of 20 morphotypes of ciliates during spring in Lake Zurich, Switzerland, and we relate their abundances to phytoplankton genera, flagellates, heterotrophic bacteria, and abiotic parameters. Interspecific relationships were analyzed by contemporaneous correlations and time-lagged co-occurrence and visualized as association networks. The contemporaneous network pointed to the pivotal role of distinct ciliate species (e.g., Balanion planctonicum, Rimostrombidium humile as primary consumers of cryptomonads, revealed a clear overclustering of mixotrophic / omnivorous species, and highlighted the role of Halteria / Pelagohalteria as important bacterivores. By contrast, time-lagged statistical approaches (like local similarity analyses, LSA proved to be inadequate for the evaluation of high-frequency sampling data. LSA led to a conspicuous inflation of significant associations, making it difficult to establish ecologically plausible interactions between ciliates and other microorganisms. Nevertheless, if adequate statistical procedures are selected, association networks can be powerful tools to formulate testable hypotheses about the autecology of only recently described ciliate species.

  17. Exploring overlapping functional units with various structure in protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Xiao-Fei Zhang

    Full Text Available Revealing functional units in protein-protein interaction (PPI networks are important for understanding cellular functional organization. Current algorithms for identifying functional units mainly focus on cohesive protein complexes which have more internal interactions than external interactions. Most of these approaches do not handle overlaps among complexes since they usually allow a protein to belong to only one complex. Moreover, recent studies have shown that other non-cohesive structural functional units beyond complexes also exist in PPI networks. Thus previous algorithms that just focus on non-overlapping cohesive complexes are not able to present the biological reality fully. Here, we develop a new regularized sparse random graph model (RSRGM to explore overlapping and various structural functional units in PPI networks. RSRGM is principally dominated by two model parameters. One is used to define the functional units as groups of proteins that have similar patterns of connections to others, which allows RSRGM to detect non-cohesive structural functional units. The other one is used to represent the degree of proteins belonging to the units, which supports a protein belonging to more than one revealed unit. We also propose a regularizer to control the smoothness between the estimators of these two parameters. Experimental results on four S. cerevisiae PPI networks show that the performance of RSRGM on detecting cohesive complexes and overlapping complexes is superior to that of previous competing algorithms. Moreover, RSRGM has the ability to discover biological significant functional units besides complexes.

  18. How People Interact in Evolving Online Affiliation Networks

    Science.gov (United States)

    Gallos, Lazaros K.; Rybski, Diego; Liljeros, Fredrik; Havlin, Shlomo; Makse, Hernán A.

    2012-07-01

    The study of human interactions is of central importance for understanding the behavior of individuals, groups, and societies. Here, we observe the formation and evolution of networks by monitoring the addition of all new links, and we analyze quantitatively the tendencies used to create ties in these evolving online affiliation networks. We show that an accurate estimation of these probabilistic tendencies can be achieved only by following the time evolution of the network. Inferences about the reason for the existence of links using statistical analysis of network snapshots must therefore be made with great caution. Here, we start by characterizing every single link when the tie was established in the network. This information allows us to describe the probabilistic tendencies of tie formation and extract meaningful sociological conclusions. We also find significant differences in behavioral traits in the social tendencies among individuals according to their degree of activity, gender, age, popularity, and other attributes. For instance, in the particular data sets analyzed here, we find that women reciprocate connections 3 times as much as men and that this difference increases with age. Men tend to connect with the most popular people more often than women do, across all ages. On the other hand, triangular tie tendencies are similar, independent of gender, and show an increase with age. These results require further validation in other social settings. Our findings can be useful to build models of realistic social network structures and to discover the underlying laws that govern establishment of ties in evolving social networks.

  19. DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network.

    Science.gov (United States)

    Mistry, Divya; Wise, Roger P; Dickerson, Julie A

    2017-01-01

    Identification of central genes and proteins in biomolecular networks provides credible candidates for pathway analysis, functional analysis, and essentiality prediction. The DiffSLC centrality measure predicts central and essential genes and proteins using a protein-protein interaction network. Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures helped identify critical genes and proteins in biomolecular networks. The proposed centrality measure, DiffSLC, combines the number of interactions of a protein and the gene coexpression values of genes from which those proteins were translated, as a weighting factor to bias the identification of essential proteins in a protein interaction network. Potentially essential proteins with low node degree are promoted through eigenvector centrality. Thus, the gene coexpression values are used in conjunction with the eigenvector of the network's adjacency matrix and edge clustering coefficient to improve essentiality prediction. The outcome of this prediction is shown using three variations: (1) inclusion or exclusion of gene co-expression data, (2) impact of different coexpression measures, and (3) impact of different gene expression data sets. For a total of seven networks, DiffSLC is compared to other centrality measures using Saccharomyces cerevisiae protein interaction networks and gene expression data. Comparisons are also performed for the top ranked proteins against the known essential genes from the Saccharomyces Gene Deletion Project, which show that DiffSLC detects more essential proteins and has a higher area under the ROC curve than other compared methods. This makes DiffSLC a stronger alternative to other centrality methods for detecting essential genes using a protein-protein interaction network that obeys centrality-lethality principle. DiffSLC is implemented using the igraph package in R, and networkx package in Python. The python package can be

  20. The interaction between network ties and business modeling : Case studies of sustainability-oriented innovations

    NARCIS (Netherlands)

    Oskam, Inge; Bossink, Bart; de Man, Ard Pieter

    2018-01-01

    A stream of literature is emerging where network development and business modeling intersect. Various authors emphasize that networks influence business models. This paper extends this stream of literature by studying two cases in which we analyze how business modeling and networking interact over

  1. The Interaction between network ties and business modeling : case studies of sustainability-oriented innovations

    NARCIS (Netherlands)

    Oskam, Inge; Bossink, Bart; de Man, Ard-Pieter

    2018-01-01

    A stream of literature is emerging where network development and business modeling intersect. Various authors emphasize that networks influence business models. This paper extends this stream of literature by studying two cases in which we analyze how business modeling and networking interact over

  2. Desertification risk in Kakheti Region, East Georgia.

    Science.gov (United States)

    Basialashvili, Tsisana; Matchavariani, Lia; Lagidze, Lamzira

    2015-01-01

    Desertification or land degradation in drylands is caused by various factors. The most important of these is climate change, a significant global ecological problem. Desertification, like erosion, as an environmental process of ecosystem degradation, is often caused by human activity. It is a common misconception that droughts cause desertification. Well-managed lands can recover from drought if the rains return. These practices help to control erosion and maintain productivity during periods when moisture is available. Traditionally, the most vulnerable territories considered under the threat of desertification in Georgia is Kakheti region (East Georgia), which has been selected as one of the priority investigation area. In Eastern Georgia, intervals of atmospheric precipitation do not coincide with the phases of water demand of plants. In recent decades as a result of more frequent droughts in Kakheti, the region has already lost hundreds, thousands of hectares of fertile land. Based on the contemporary climate warming projections, the temperature is expected to increase and precipitation to decrease. This will lead to an increase in evaporation and reduction of river flow. Under such conditions the danger of desertification is evident. To mitigate the negative effects of desertification, it is recommended to put forward set of adaptation activities through rehabilitation of water use systems, prevention of loss of water, reconstruction and expansion of irrigation canals, accumulation of unused autumn-winter river water and spring floods in reservoirs, developing an optimal scheme of distributing water resources among water users, device windbreaks and work on breeding of drought resistant varieties, preparation of water volume forecasts of rivers and their role in planning of water use; application of apply drip and sprinkler irrigation, using artificial precipitation following increase as a result of active influence on clouds. All these activities will provide

  3. Social network analysis of character interaction in the Stargate and Star Trek television series

    Science.gov (United States)

    Tan, Melody Shi Ai; Ujum, Ephrance Abu; Ratnavelu, Kuru

    This paper undertakes a social network analysis of two science fiction television series, Stargate and Star Trek. Television series convey stories in the form of character interaction, which can be represented as “character networks”. We connect each pair of characters that exchanged spoken dialogue in any given scene demarcated in the television series transcripts. These networks are then used to characterize the overall structure and topology of each series. We find that the character networks of both series have similar structure and topology to that found in previous work on mythological and fictional networks. The character networks exhibit the small-world effects but found no significant support for power-law. Since the progression of an episode depends to a large extent on the interaction between each of its characters, the underlying network structure tells us something about the complexity of that episode’s storyline. We assessed the complexity using techniques from spectral graph theory. We found that the episode networks are structured either as (1) closed networks, (2) those containing bottlenecks that connect otherwise disconnected clusters or (3) a mixture of both.

  4. Inclusive Education in Georgia: Current Progress and Challenges

    Directory of Open Access Journals (Sweden)

    Nikoloz Kavelashvili

    2017-05-01

    Full Text Available Purpose and Originality: The paper provides a realistic picture about how the implementation process of inclusive education in Georgia is developing, about the problems that are encountered together with what needs are to be fulfilled for stimulating the process. Today’s challenge in the country is to make inclusive practices available to everybody, everywhere and all the time. This article discusses the status of the efforts being made to meet this challenge. In the course of that discussion, some comprehensive changes will be described that systemic efforts of school improvement must achieve to continue making progress towards fully inclusive learning. Method: The study was conducted in Georgia. A qualitative research design was employed along with closed-ended and open-ended questionnaires, which allowed participants to express their point of views, skills and knowledge. Data collection methods were applied: semi-structured interviews and observation on respondents. Results: The study uncovers those challenges that obstruct the implementation process: indifferent attitudes of teachers and parents towards inclusion, absence of self-awareness to the issue amongst educators, slightest involvement of parents and need to infrastructural development. Society: The results should raise the awareness of the population of Georgia as well as increase the understanding of the problem. Limitations / further research: There were quite enough informants on the school level (special teachers, principals, however, there are still many other possible respondents who could add something valuable to a better understanding of the process of inclusion at schools. The theoretical approach employed in the study and the empirical research could be validated.

  5. Higher-Order Synaptic Interactions Coordinate Dynamics in Recurrent Networks.

    Directory of Open Access Journals (Sweden)

    Brendan Chambers

    2016-08-01

    Full Text Available Linking synaptic connectivity to dynamics is key to understanding information processing in neocortex. Circuit dynamics emerge from complex interactions of interconnected neurons, necessitating that links between connectivity and dynamics be evaluated at the network level. Here we map propagating activity in large neuronal ensembles from mouse neocortex and compare it to a recurrent network model, where connectivity can be precisely measured and manipulated. We find that a dynamical feature dominates statistical descriptions of propagating activity for both neocortex and the model: convergent clusters comprised of fan-in triangle motifs, where two input neurons are themselves connected. Fan-in triangles coordinate the timing of presynaptic inputs during ongoing activity to effectively generate postsynaptic spiking. As a result, paradoxically, fan-in triangles dominate the statistics of spike propagation even in randomly connected recurrent networks. Interplay between higher-order synaptic connectivity and the integrative properties of neurons constrains the structure of network dynamics and shapes the routing of information in neocortex.

  6. Auditing Medical Records Accesses via Healthcare Interaction Networks

    Science.gov (United States)

    Chen, You; Nyemba, Steve; Malin, Bradley

    2012-01-01

    Healthcare organizations are deploying increasingly complex clinical information systems to support patient care. Traditional information security practices (e.g., role-based access control) are embedded in enterprise-level systems, but are insufficient to ensure patient privacy. This is due, in part, to the dynamic nature of healthcare, which makes it difficult to predict which care providers need access to what and when. In this paper, we show that modeling operations at a higher level of granularity (e.g., the departmental level) are stable in the context of a relational network, which may enable more effective auditing strategies. We study three months of access logs from a large academic medical center to illustrate that departmental interaction networks exhibit certain invariants, such as the number, strength, and reciprocity of relationships. We further show that the relations extracted from the network can be leveraged to assess the extent to which a patient’s care satisfies expected organizational behavior. PMID:23304277

  7. Sex Bias in Georgia High School Economics Textbooks.

    Science.gov (United States)

    Blankenship, Glen; Hahn, Carole L.

    1982-01-01

    Analyzes 17 secondary level economics textbooks for sex bias. All of the texts reviewed are on Georgia's approved textbook list. Without exception, each of the texts is guilty of sex bias, although to varying degrees. The method used in analyzing the texts is explained. (RM)

  8. Temporal variation in bat-fruit interactions: Foraging strategies influence network structure over time

    Science.gov (United States)

    Zapata-Mesa, Natalya; Montoya-Bustamante, Sebastián; Murillo-García, Oscar E.

    2017-11-01

    Mutualistic interactions, such as seed dispersal, are important for the maintenance of structure and stability of tropical communities. However, there is a lack of information about spatial and temporal variation in plant-animal interaction networks. Thus, our goal was to assess the effect of bat's foraging strategies on temporal variation in the structure and robustness of bat-fruit networks in both a dry and a rain tropical forest. We evaluated monthly variation in bat-fruit networks by using seven structure metrics: network size, average path length, nestedness, modularity, complementary specialization, normalized degree and betweenness centrality. Seed dispersal networks showed variations in size, species composition and modularity; did not present nested structures and their complementary specialization was high compared to other studies. Both networks presented short path lengths, and a constantly high robustness, despite their monthly variations. Sedentary bat species were recorded during all the study periods and occupied more central positions than nomadic species. We conclude that foraging strategies are important structuring factors that affect the dynamic of networks by determining the functional roles of frugivorous bats over time; thus sedentary bats are more important than nomadic species for the maintenance of the network structure, and their conservation is a must.

  9. Using Their Own People Against Them: Russia’s Exploitation of Ethnicity in Georgia and Ukraine

    Science.gov (United States)

    2015-12-01

    Caucasus, from Nagorno-Karabakh to Chechnya . Georgia, once a prosperous Soviet Socialist Republic, could not escape the chaos. During this first phase...Afghanistan, Chechnya , and Georgia, but others were simply politicized rightist nationalists eager to export their ideology.222 These volunteers were

  10. The role of exon shuffling in shaping protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    França Gustavo S

    2010-12-01

    Full Text Available Abstract Background Physical protein-protein interaction (PPI is a critical phenomenon for the function of most proteins in living organisms and a significant fraction of PPIs are the result of domain-domain interactions. Exon shuffling, intron-mediated recombination of exons from existing genes, is known to have been a major mechanism of domain shuffling in metazoans. Thus, we hypothesized that exon shuffling could have a significant influence in shaping the topology of PPI networks. Results We tested our hypothesis by compiling exon shuffling and PPI data from six eukaryotic species: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Cryptococcus neoformans and Arabidopsis thaliana. For all four metazoan species, genes enriched in exon shuffling events presented on average higher vertex degree (number of interacting partners in PPI networks. Furthermore, we verified that a set of protein domains that are simultaneously promiscuous (known to interact to multiple types of other domains, self-interacting (able to interact with another copy of themselves and abundant in the genomes presents a stronger signal for exon shuffling. Conclusions Exon shuffling appears to have been a recurrent mechanism for the emergence of new PPIs along metazoan evolution. In metazoan genomes, exon shuffling also promoted the expansion of some protein domains. We speculate that their promiscuous and self-interacting properties may have been decisive for that expansion.

  11. Frameworks for Understanding the Nature of Interactions, Networking, and Community in a Social Networking Site for Academic Practice

    Directory of Open Access Journals (Sweden)

    Grainne Conole

    2011-03-01

    Full Text Available This paper describes a new social networking site, Cloudworks, which has been developed to enable discussion and sharing of learning and teaching ideas/designs and to promote reflective academic practice. The site aims to foster new forms of social and participatory practices (peer critiquing, sharing, user-generated content, aggregation, and personalisation within an educational context. One of the key challenges in the development of the site has been to understand the user interactions and the changing patterns of user behaviour as it evolves. The paper explores the extent to which four frameworks that have been used in researching networked learning contexts can provide insights into the patterns of user behaviour that we see in Cloudworks. The paper considers this within the current debate about the new types of interactions, networking, and community being observed as users adapt to and appropriate new technologies.

  12. Characterizing Social Interaction in Tobacco-Oriented Social Networks: An Empirical Analysis.

    Science.gov (United States)

    Liang, Yunji; Zheng, Xiaolong; Zeng, Daniel Dajun; Zhou, Xingshe; Leischow, Scott James; Chung, Wingyan

    2015-06-19

    Social media is becoming a new battlefield for tobacco "wars". Evaluating the current situation is very crucial for the advocacy of tobacco control in the age of social media. To reveal the impact of tobacco-related user-generated content, this paper characterizes user interaction and social influence utilizing social network analysis and information theoretic approaches. Our empirical studies demonstrate that the exploding pro-tobacco content has long-lasting effects with more active users and broader influence, and reveal the shortage of social media resources in global tobacco control. It is found that the user interaction in the pro-tobacco group is more active, and user-generated content for tobacco promotion is more successful in obtaining user attention. Furthermore, we construct three tobacco-related social networks and investigate the topological patterns of these tobacco-related social networks. We find that the size of the pro-tobacco network overwhelms the others, which suggests a huge number of users are exposed to the pro-tobacco content. These results indicate that the gap between tobacco promotion and tobacco control is widening and tobacco control may be losing ground to tobacco promotion in social media.

  13. Insights into the fold organization of TIM barrel from interaction energy based structure networks.

    Science.gov (United States)

    Vijayabaskar, M S; Vishveshwara, Saraswathi

    2012-01-01

    There are many well-known examples of proteins with low sequence similarity, adopting the same structural fold. This aspect of sequence-structure relationship has been extensively studied both experimentally and theoretically, however with limited success. Most of the studies consider remote homology or "sequence conservation" as the basis for their understanding. Recently "interaction energy" based network formalism (Protein Energy Networks (PENs)) was developed to understand the determinants of protein structures. In this paper we have used these PENs to investigate the common non-covalent interactions and their collective features which stabilize the TIM barrel fold. We have also developed a method of aligning PENs in order to understand the spatial conservation of interactions in the fold. We have identified key common interactions responsible for the conservation of the TIM fold, despite high sequence dissimilarity. For instance, the central beta barrel of the TIM fold is stabilized by long-range high energy electrostatic interactions and low-energy contiguous vdW interactions in certain families. The other interfaces like the helix-sheet or the helix-helix seem to be devoid of any high energy conserved interactions. Conserved interactions in the loop regions around the catalytic site of the TIM fold have also been identified, pointing out their significance in both structural and functional evolution. Based on these investigations, we have developed a novel network based phylogenetic analysis for remote homologues, which can perform better than sequence based phylogeny. Such an analysis is more meaningful from both structural and functional evolutionary perspective. We believe that the information obtained through the "interaction conservation" viewpoint and the subsequently developed method of structure network alignment, can shed new light in the fields of fold organization and de novo computational protein design.

  14. Layered vanadyl (IV) nitroprusside: Magnetic interaction through a network of hydrogen bonds

    Energy Technology Data Exchange (ETDEWEB)

    Gil, D.M. [Instituto de Química Física, Facultad de Bioquímica, Química y Farmacia, Universidad Nacional de Tucumán, San Lorenzo 456, T4000CAN San Miguel de Tucumán (Argentina); Osiry, H. [Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada, Unidad Legaria, Instituto Politécnico Nacional, México (Mexico); Pomiro, F.; Varetti, E.L. [CEQUINOR (CONICET-UNLP), Facultad de Ciencias Exactas, Universidad Nacional de La Plata, 47 and 115, 1900, La Plata (Argentina); Carbonio, R.E. [INFIQC – CONICET, Departamento de Físico Química, Facultad de Ciencias Químicas, Universidad Nacional de Córdoba, Haya de la Torre esq, Medina Allende, Ciudad Universitaria, X5000HUA Córdoba (Argentina); Alejandro, R.R. [Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada, Unidad Legaria, Instituto Politécnico Nacional, México (Mexico); Ben Altabef, A. [INQUINOA-UNT-CONICET, Instituto de Química Física, Facultad de Bioquímica, Química y Farmacia, Universidad Nacional de Tucumán, San Lorenzo 456, T4000CAN San Miguel de Tucumán (Argentina); and others

    2016-07-15

    The hydrogen bond and π-π stacking are two non-covalent interactions able to support cooperative magnetic ordering between paramagnetic centers. This contribution reports the crystal structure and related magnetic properties for VO[Fe(CN){sub 5}NO]·2H{sub 2}O, which has a layered structure. This solid crystallizes with an orthorhombic unit cell, in the Pna2{sub 1} space group, with cell parameters a=14.1804(2), b=10.4935(1), c=7.1722(8) Å and four molecules per unit cell (Z=4). Its crystal structure was solved and refined from powder X-ray diffraction data. Neighboring layers remain linked through a network of hydrogen bonds involving a water molecule coordinated to the axial position for the V atom and the unbridged axial NO and CN ligands. An uncoordinated water molecule is found forming a triple bridge between these last two ligands and the coordinated water molecule. The magnetic measurements, recorded down to 2 K, shows a ferromagnetic interaction between V atoms located at neighboring layers, with a Curie-Weiss constant of 3.14 K. Such ferromagnetic behavior was interpreted as resulting from a superexchange interaction through the network of strong OH····O{sub H2O}, OH····N{sub CN}, and OH····O{sub NO} hydrogen bonds that connects neighboring layers. The interaction within the layer must be of antiferromagnetic nature and it was detected close to 2 K. - Graphical abstract: Coordination environment for the metals in vanadyl (II) nitroprusside dihydrate. Display Omitted - Highlights: • Crystal structure of vanadyl nitroprusside dehydrate. • Network of hydrogen bonds. • Magnetic interactions through a network of hydrogen bonds. • Layered transition metal nitroprussides.

  15. Building Social Interactions as a Creation of Networks in an RDF Repository

    Directory of Open Access Journals (Sweden)

    Eun G Park

    2018-02-01

    Full Text Available Humanities scholars are not likely to be thinking about their research findings as data, and the predominant models of organizing documents remain generally archival or bibliographic in nature for text-based documents. Although the linked data movement has greatly influenced information organization and search queries on the Web, in comparison to other fields, the adoption of the linked data approach to humanities collections is unequally paced.  This study intends to explain how people or actors make social interactions, and how social interactions are formed in a type of network through the example of the Making Publics (MaPs project. The objective of the MaPs project is to build collaborative common environments for tracing social interactions between people, things, places and times. To build social interactions, the Networked Event Model was designed in a collaborative environment. Events were defined as six types of nodes (e.g., people, organizations, places, things, events, and literals in the RDF (Resource Description Framework triple statements. The interaction vocabulary list is made of 173 verbs and predicates, offering 510 traceable events. The RDF repository runs on a Sesame server and MySQL architecture. Users can use digital tools to select and document events and visually present the selected events in interactive social web forms. The MaPs project sought to extract the network extant in the works of prose in large collaborative humanities documents. In this way, the dissemination of and access to humanities data can be made more connectable, available and accessible to both academic and non-academic communities.

  16. Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0.

    Directory of Open Access Journals (Sweden)

    Brian R Granger

    2016-04-01

    Full Text Available The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space, a dynamic stoichiometric modeling framework. Using VisANT's unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu.

  17. Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0.

    Science.gov (United States)

    Granger, Brian R; Chang, Yi-Chien; Wang, Yan; DeLisi, Charles; Segrè, Daniel; Hu, Zhenjun

    2016-04-01

    The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu.

  18. An Atomic Force Microscopy Study of the Interactions Involving Polymers and Silane Networks

    Directory of Open Access Journals (Sweden)

    Rodrigo L. Oréfice

    1998-12-01

    Full Text Available ABSTRACT: Silane coupling agents have been frequently used as interfacial agents in polymer composites to improve interfacial strength and resistance to fluid migration. Although the capability of these agents in improving properties and performance of composites has been reported, there are still many uncertainties regarding the processing-structure-property relationships and the mechanisms of coupling developed by silane agents. In this work, an Atomic Force Microscope (AFM was used to measure interactions between polymers and silica substrates, where silane networks with a series of different structures were processed. The influence of the structure of silane networks on the interactions with polymers was studied and used to determine the mechanisms involved in the coupling phenomenon. The AFM results showed that phenomena such as chain penetration, entanglements, intersegment bonding, chain conformation in the vicinities of rigid surfaces were identified as being relevant for the overall processes of adhesion and adsorption of polymeric chains within a silane network. AFM adhesion curves showed that penetration of polymeric chains through a more open silane network can lead to higher levels of interactions between polymer and silane agents.

  19. Social networks, social interactions, and activity-travel behavior: a framework for microsimulation

    NARCIS (Netherlands)

    Arentze, T.A.; Timmermans, H.J.P.

    2007-01-01

    We argue that the social networks and activity-travel patterns of people interact and coevolve over time. Through social interaction, people exchange information about activity-travel choice alternatives and adapt their latent and overt preferences for alternatives to each other. At the same time,

  20. Inclusive Education in Georgia: Current Trends and Challenges

    Science.gov (United States)

    Tchintcharauli, Tinatin; Javakhishvili, Nino

    2017-01-01

    This article presents the first comprehensive study of the Georgian inclusive education system launched nationwide in 2006. An internationally recognised tool, the "Pathway to Inclusion--Barometer of Inclusive Education", was applied within the country to highlight the current position of inclusive education in Georgia. The collected…

  1. Dollarization in transition economies: new evidence from Georgia

    Czech Academy of Sciences Publication Activity Database

    Aslanidi, Olga

    -, č. 366 (2008), s. 1-31 ISSN 1211-3298 R&D Projects: GA MŠk LC542 Institutional research plan: CEZ:AV0Z70850503 Keywords : dollarization * Georgia * money-in-utility-function Subject RIV: AH - Economics http://www.cerge-ei.cz/pdf/wp/Wp366.pdf

  2. The specificity of host-bat fly interaction networks across vegetation and seasonal variation.

    Science.gov (United States)

    Zarazúa-Carbajal, Mariana; Saldaña-Vázquez, Romeo A; Sandoval-Ruiz, César A; Stoner, Kathryn E; Benitez-Malvido, Julieta

    2016-10-01

    Vegetation type and seasonality promote changes in the species composition and abundance of parasite hosts. However, it is poorly known how these variables affect host-parasite interaction networks. This information is important to understand the dynamics of parasite-host relationships according to biotic and abiotic changes. We compared the specialization of host-bat fly interaction networks, as well as bat fly and host species composition between upland dry forest and riparian forest and between dry and rainy seasons in a tropical dry forest in Jalisco, Mexico. Bat flies were surveyed by direct collection from bats. Our results showed that host-bat fly interaction networks were more specialized in upland dry forest compared to riparian forest. Bat fly species composition was different between the dry and rainy seasons, while host species composition was different between upland dry forest and riparian forest. The higher specialization in upland dry forest could be related to the differences in bat host species composition and their respective roosting habits. Variation in the composition of bat fly species between dry and rainy seasons coincides with the seasonal shifts in their species richness. Our study confirms the high specialization of host-bat fly interactions and shows the importance of biotic and abiotic factors to understand the dynamics of parasite-host interactions.

  3. Predicting drug?drug interactions through drug structural similarities and interaction networks incorporating pharmacokinetics and pharmacodynamics knowledge

    OpenAIRE

    Takeda, Takako; Hao, Ming; Cheng, Tiejun; Bryant, Stephen H.; Wang, Yanli

    2017-01-01

    Drug?drug interactions (DDIs) may lead to adverse effects and potentially result in drug withdrawal from the market. Predicting DDIs during drug development would help reduce development costs and time by rigorous evaluation of drug candidates. The primary mechanisms of DDIs are based on pharmacokinetics (PK) and pharmacodynamics (PD). This study examines the effects of 2D structural similarities of drugs on DDI prediction through interaction networks including both PD and PK knowledge. Our a...

  4. 78 FR 62357 - Georgia Power Company; Notice of Application Accepted for Filing, Soliciting Motions To Intervene...

    Science.gov (United States)

    2013-10-21

    ... located on the Chattahoochee River, along the Georgia-Alabama border, in Harris County, Georgia, and Lee...-foot-high concrete gravity intake structure, equipped with four vertical lift steel intake gates... canal leading to a 177-foot-long concrete gravity intake structure; (3) two penstocks; and (4) a...

  5. Crucial role of strategy updating for coexistence of strategies in interaction networks

    NARCIS (Netherlands)

    Zhang, Jianlei; Zhang, Chunyan; Cao, Ming; Weissing, Franz J.

    2015-01-01

    Network models are useful tools for studying the dynamics of social interactions in a structured population. After a round of interactions with the players in their local neighborhood, players update their strategy based on the comparison of their own payoff with the payoff of one of their

  6. CONCERNING THE NETWORKING INTERACTION EXPERIENCE OF TEACHERS AND STUDENTS OF PEDAGOGICAL UNIVERSITY

    Directory of Open Access Journals (Sweden)

    E. A. Dmitrieva

    2015-01-01

    Full Text Available The purpose of the research is to identify the possibilities for the formation knowledge and practical skills related to the use of the professional activity of software and network resource of teaching communities in the pedagogical sphere.Methods. The methods involve the analysis of the literary sources, regulatory documents, Internet resources within the researched problem; an analysis of the practical experience of teachers of secondary schools, work of high school teachers and establishment of training teachers on the research problem; the experimental work and monitoring the learning process.Results. The process of teachers’ training inYaroslavl, in particular preparation of students-biologists at theYaroslavlStatePedagogicalUniversityis reflected. Activity of network pedagogical community of Yaroslavl is considered as a platform for network interaction; the analysis of such platform, use of its resources, and also conversations with subject teachers and students have shown that the given electronic and communication resources cause a great interest for practicing teachers and future experts, however, they not always possess necessary knowledge and abilities concerning its operation.Scientific novelty. The author describes in detail the process of forming a competence of networking of professional interaction in terms of its methodological support that is relevant to the educational process, both in the high school, and post-graduate education.Practical significance. The research implementations can be useful while developing specific guidelines to explain the content and methodology of the training network of professional interaction with examples of practicing teachers and students ofPedagogicalUniversity– future teachers of biology.The article is addressed to researchers, dealing with networking, specialists of teaching service centers (institutions of educational development, the practicing subject teachers and teachers of high

  7. The poverty effect of remittance flows: evidence from Georgia

    Czech Academy of Sciences Publication Activity Database

    Uzagalieva, Ainura

    -, 11/2008 (2008), s. 1-22 ISSN N Institutional research plan: CEZ:AV0Z70850503 Keywords : poverty * remittance flows * Georgia Subject RIV: AH - Economics http://www.deg.uac.pt/~ceeapla/pt/pdf/papers/Paper11-2008.pdf

  8. Network dynamics with BrainX(3): a large-scale simulation of the human brain network with real-time interaction.

    Science.gov (United States)

    Arsiwalla, Xerxes D; Zucca, Riccardo; Betella, Alberto; Martinez, Enrique; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F M J

    2015-01-01

    BrainX(3) is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX(3) in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX(3) can thus be used as a novel immersive platform for exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas.

  9. Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

    Science.gov (United States)

    Arsiwalla, Xerxes D.; Zucca, Riccardo; Betella, Alberto; Martinez, Enrique; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F. M. J.

    2015-01-01

    BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX3 can thus be used as a novel immersive platform for exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas. PMID:25759649

  10. Network Dynamics with BrainX3: A Large-Scale Simulation of the Human Brain Network with Real-Time Interaction

    Directory of Open Access Journals (Sweden)

    Xerxes D. Arsiwalla

    2015-02-01

    Full Text Available BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX3 can thus be used as a novel immersive platform for real-time exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably, due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas.

  11. Global innovation networks and university-firm interactions: an exploratory survey analysis

    Directory of Open Access Journals (Sweden)

    Gustavo Britto

    2015-02-01

    Full Text Available The literature on Global Innovation Networks has contributed to identify changes in the innovation activities of multinational corporations. Although university-firm interactions are seen as an important factor for the emergence of GINs, their role has received limited attention. This paper aims to fill this gap in two ways. First, it carries out an exploratory analysis of an original survey dataset, of firms in three industrial sectors from nine developed and developing countries. Second, the paper analyses whether the role of universities in global innovation networks is related to national systems of innovation with varying degrees of maturity. Multiple correspondence analysis and a Probit model are used to establish the relevance of key factors in driving GINs. The results identify distinctive profiles constructed mainly according to firm characteristics, but reflecting country specific patterns of association. The Probit model confirms that internationalization processes and the existence of local interactions substantially increase the probability of interactions with international institutions.

  12. Network structure beyond food webs: mapping non-trophic and trophic interactions on Chilean rocky shores.

    Science.gov (United States)

    Sonia Kéfi; Berlow, Eric L; Wieters, Evie A; Joppa, Lucas N; Wood, Spencer A; Brose, Ulrich; Navarrete, Sergio A

    2015-01-01

    How multiple types of non-trophic interactions map onto trophic networks in real communities remains largely unknown. We present the first effort, to our knowledge, describing a comprehensive ecological network that includes all known trophic and diverse non-trophic links among >100 coexisting species for the marine rocky intertidal community of the central Chilean coast. Our results suggest that non-trophic interactions exhibit highly nonrandom structures both alone and with respect to food web structure. The occurrence of different types of interactions, relative to all possible links, was well predicted by trophic structure and simple traits of the source and target species. In this community, competition for space and positive interactions related to habitat/refuge provisioning by sessile and/or basal species were by far the most abundant non-trophic interactions. If these patterns are orroborated in other ecosystems, they may suggest potentially important dynamic constraints on the combined architecture of trophic and non-trophic interactions. The nonrandom patterning of non-trophic interactions suggests a path forward for developing a more comprehensive ecological network theory to predict the functioning and resilience of ecological communities.

  13. Reconstructing past ecological networks: the reconfiguration of seed-dispersal interactions after megafaunal extinction.

    Science.gov (United States)

    Pires, Mathias M; Galetti, Mauro; Donatti, Camila I; Pizo, Marco A; Dirzo, Rodolfo; Guimarães, Paulo R

    2014-08-01

    The late Quaternary megafaunal extinction impacted ecological communities worldwide, and affected key ecological processes such as seed dispersal. The traits of several species of large-seeded plants are thought to have evolved in response to interactions with extinct megafauna, but how these extinctions affected the organization of interactions in seed-dispersal systems is poorly understood. Here, we combined ecological and paleontological data and network analyses to investigate how the structure of a species-rich seed-dispersal network could have changed from the Pleistocene to the present and examine the possible consequences of such changes. Our results indicate that the seed-dispersal network was organized into modules across the different time periods but has been reconfigured in different ways over time. The episode of megafaunal extinction and the arrival of humans changed how seed dispersers were distributed among network modules. However, the recent introduction of livestock into the seed-dispersal system partially restored the original network organization by strengthening the modular configuration. Moreover, after megafaunal extinctions, introduced species and some smaller native mammals became key components for the structure of the seed-dispersal network. We hypothesize that such changes in network structure affected both animal and plant assemblages, potentially contributing to the shaping of modern ecological communities. The ongoing extinction of key large vertebrates will lead to a variety of context-dependent rearranged ecological networks, most certainly affecting ecological and evolutionary processes.

  14. The poverty effect of remittance flows: evidence from Georgia

    Czech Academy of Sciences Publication Activity Database

    Uzagalieva, Ainura; Menezes, A. G.

    -, 06/2009 (2009), s. 1-44 ISSN N Institutional research plan: CEZ:AV0Z70850503 Keywords : poverty * remittance flows * Georgia Subject RIV: AH - Economics http://www.deg.uac.pt/~ceeapla/pt/pdf/ paper s/ Paper 06-2009.pdf

  15. Comparison of asthma prevalence among African American teenage youth attending public high schools in rural Georgia and urban Detroit.

    Science.gov (United States)

    Ownby, Dennis R; Tingen, Martha S; Havstad, Suzanne; Waller, Jennifer L; Johnson, Christine C; Joseph, Christine L M

    2015-09-01

    The high prevalence of asthma among urban African American (AA) populations has attracted research attention, whereas the prevalence among rural AA populations is poorly documented. We sought to compare the prevalence of asthma among AA youth in rural Georgia and urban Detroit, Michigan. The prevalence of asthma was compared in population-based samples of 7297 youth attending Detroit public high schools and in 2523 youth attending public high schools in rural Georgia. Current asthma was defined as a physician diagnosis and symptoms in the previous 12 months. Undiagnosed asthma was defined as multiple respiratory symptoms in the previous 12 months without a physician diagnosis. In Detroit, 6994 (95.8%) youth were AA compared with 1514 (60.0%) in Georgia. Average population density in high school postal codes was 5628 people/mile(2) in Detroit and 45.1 people/mile(2) in Georgia. The percentages of poverty and of students qualifying for free or reduced lunches were similar in both areas. The prevalence of current diagnosed asthma among AA youth in Detroit and Georgia was similar: 15.0% (95% CI, 14.1-15.8) and 13.7% (95% CI, 12.0-17.1) (P = .22), respectively. The prevalence of undiagnosed asthma in AA youth was 8.0% in Detroit and 7.5% in Georgia (P = .56). Asthma symptoms were reported more frequently among those with diagnosed asthma in Detroit, whereas those with undiagnosed asthma in Georgia reported more symptoms. Among AA youth living in similar socioeconomic circumstances, asthma prevalence is as high in rural Georgia as it is in urban Detroit, suggesting that urban residence is not an asthma risk factor. Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

  16. Revisiting date and party hubs: novel approaches to role assignment in protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Sumeet Agarwal

    2010-06-01

    Full Text Available The idea of "date" and "party" hubs has been influential in the study of protein-protein interaction networks. Date hubs display low co-expression with their partners, whilst party hubs have high co-expression. It was proposed that party hubs are local coordinators whereas date hubs are global connectors. Here, we show that the reported importance of date hubs to network connectivity can in fact be attributed to a tiny subset of them. Crucially, these few, extremely central, hubs do not display particularly low expression correlation, undermining the idea of a link between this quantity and hub function. The date/party distinction was originally motivated by an approximately bimodal distribution of hub co-expression; we show that this feature is not always robust to methodological changes. Additionally, topological properties of hubs do not in general correlate with co-expression. However, we find significant correlations between interaction centrality and the functional similarity of the interacting proteins. We suggest that thinking in terms of a date/party dichotomy for hubs in protein interaction networks is not meaningful, and it might be more useful to conceive of roles for protein-protein interactions rather than for individual proteins.

  17. Online Social Network Interactions:

    Directory of Open Access Journals (Sweden)

    Hui-Jung Chang

    2018-01-01

    Full Text Available A cross-cultural comparison of social networking structure on McDonald’s Facebook fan sites between Taiwan and the USA was conducted utilizing the individualism/collectivism dimension proposed by Hofstede. Four network indicators are used to describe the network structure of McDonald’s Facebook fan sites: size, density, clique and centralization. Individuals who post on both Facebook sites for the year of 2012 were considered as network participants for the purpose of the study. Due to the huge amount of data, only one thread of postings was sampled from each month of the year of 2012. The final data consists of 1002 postings written by 896 individuals and 5962 postings written by 5532 individuals from Taiwan and the USA respectively. The results indicated that the USA McDonald’s Facebook fan network has more fans, while Taiwan’s McDonald’s Facebook fan network is more densely connected. Cliques did form among the overall multiplex and within the individual uniplex networks in two countries, yet no significant differences were found between them. All the fan networks in both countries are relatively centralized, mostly on the site operators.

  18. CombiMotif: A new algorithm for network motifs discovery in protein-protein interaction networks

    Science.gov (United States)

    Luo, Jiawei; Li, Guanghui; Song, Dan; Liang, Cheng

    2014-12-01

    Discovering motifs in protein-protein interaction networks is becoming a current major challenge in computational biology, since the distribution of the number of network motifs can reveal significant systemic differences among species. However, this task can be computationally expensive because of the involvement of graph isomorphic detection. In this paper, we present a new algorithm (CombiMotif) that incorporates combinatorial techniques to count non-induced occurrences of subgraph topologies in the form of trees. The efficiency of our algorithm is demonstrated by comparing the obtained results with the current state-of-the art subgraph counting algorithms. We also show major differences between unicellular and multicellular organisms. The datasets and source code of CombiMotif are freely available upon request.

  19. 75 FR 17742 - Filing Dates for the Georgia Special Election in the 9th Congressional District

    Science.gov (United States)

    2010-04-07

    ... 9th Congressional District AGENCY: Federal Election Commission. ACTION: Notice of filing dates for special election. SUMMARY: Georgia has scheduled a special general election on May 11, 2010, to fill the U... participate in the Georgia Special General and Special Runoff Elections shall file a 12-day Pre-General Report...

  20. The function of communities in protein interaction networks at multiple scales

    Directory of Open Access Journals (Sweden)

    Jones Nick S

    2010-07-01

    Full Text Available Abstract Background If biology is modular then clusters, or communities, of proteins derived using only protein interaction network structure should define protein modules with similar biological roles. We investigate the link between biological modules and network communities in yeast and its relationship to the scale at which we probe the network. Results Our results demonstrate that the functional homogeneity of communities depends on the scale selected, and that almost all proteins lie in a functionally homogeneous community at some scale. We judge functional homogeneity using a novel test and three independent characterizations of protein function, and find a high degree of overlap between these measures. We show that a high mean clustering coefficient of a community can be used to identify those that are functionally homogeneous. By tracing the community membership of a protein through multiple scales we demonstrate how our approach could be useful to biologists focusing on a particular protein. Conclusions We show that there is no one scale of interest in the community structure of the yeast protein interaction network, but we can identify the range of resolution parameters that yield the most functionally coherent communities, and predict which communities are most likely to be functionally homogeneous.

  1. Bipartite networks improve understanding of effects of waterbody size and angling method on angler–fish interactions

    Science.gov (United States)

    Chizinski, Christopher J.; Martin, Dustin R.; Shizuka, Daizaburo; Pope, Kevin L.

    2018-01-01

    Networks used to study interactions could provide insights to fisheries. We compiled data from 27 297 interviews of anglers across waterbodies that ranged in size from 1 to 12 113 ha. Catch rates of fish species among anglers grouped by species targeted generally differed between angling methods (bank or boat). We constructed angler–catch bipartite networks (angling method specific) between anglers and fish and measured several network metrics. There was considerable variation in networks among waterbodies, with multiple metrics influenced by waterbody size. Number of species-targeting angler groups and number of fish species caught increased with increasing waterbody size. Mean number of links for species-targeting angler groups and fish species caught also increased with waterbody size. Connectance (realized proportion of possible links) of angler–catch interaction networks decreased slower for boat anglers than for bank anglers with increasing waterbody size. Network specialization (deviation of number of interactions from expected) was not significantly related to waterbody size or angling methods. Application of bipartite networks in fishery science requires careful interpretation of outputs, especially considering the numerous confounding factors prevalent in recreational fisheries.

  2. Combining many interaction networks to predict gene function and analyze gene lists.

    Science.gov (United States)

    Mostafavi, Sara; Morris, Quaid

    2012-05-01

    In this article, we review how interaction networks can be used alone or in combination in an automated fashion to provide insight into gene and protein function. We describe the concept of a "gene-recommender system" that can be applied to any large collection of interaction networks to make predictions about gene or protein function based on a query list of proteins that share a function of interest. We discuss these systems in general and focus on one specific system, GeneMANIA, that has unique features and uses different algorithms from the majority of other systems. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Sequence memory based on coherent spin-interaction neural networks.

    Science.gov (United States)

    Xia, Min; Wong, W K; Wang, Zhijie

    2014-12-01

    Sequence information processing, for instance, the sequence memory, plays an important role on many functions of brain. In the workings of the human brain, the steady-state period is alterable. However, in the existing sequence memory models using heteroassociations, the steady-state period cannot be changed in the sequence recall. In this work, a novel neural network model for sequence memory with controllable steady-state period based on coherent spininteraction is proposed. In the proposed model, neurons fire collectively in a phase-coherent manner, which lets a neuron group respond differently to different patterns and also lets different neuron groups respond differently to one pattern. The simulation results demonstrating the performance of the sequence memory are presented. By introducing a new coherent spin-interaction sequence memory model, the steady-state period can be controlled by dimension parameters and the overlap between the input pattern and the stored patterns. The sequence storage capacity is enlarged by coherent spin interaction compared with the existing sequence memory models. Furthermore, the sequence storage capacity has an exponential relationship to the dimension of the neural network.

  4. Accessing Wireless Sensor Networks Via Dynamically Reconfigurable Interaction Models

    Directory of Open Access Journals (Sweden)

    Maria Cecília Gomes

    2012-12-01

    Full Text Available The Wireless Sensor Networks (WSNs technology is already perceived as fundamental for science across many domains, since it provides a low cost solution for environment monitoring. WSNs representation via the service concept and its inclusion in Web environments, e.g. through Web services, supports particularly their open/standard access and integration. Although such Web enabled WSNs simplify data access, network parameterization and aggregation, the existing interaction models and run-time adaptation mechanisms available to clients are still scarce. Nevertheless, applications increasingly demand richer and more flexible accesses besides the traditional client/server. For instance, applications may require a streaming model in order to avoid sequential data requests, or the asynchronous notification of subscribed data through the publish/subscriber. Moreover, the possibility to automatically switch between such models at runtime allows applications to define flexible context-based data acquisition. To this extent, this paper discusses the relevance of the session and pattern abstractions on the design of a middleware prototype providing richer and dynamically reconfigurable interaction models to Web enabled WSNs.

  5. The paradox of caffeine-zolpidem interaction: a network analysis.

    Science.gov (United States)

    Myslobodsky, Michael

    2009-10-01

    A widely prescribed and potent short-acting hypnotic, zolpidem has become the mainstay for the treatment of middle-of-the-night sleeplessness. It is expected to be antagonized by caffeine. Paradoxically, in some cases caffeine appears to slightly enhance zolpidem sedation. The pharmacokinetic and pharmacodynamic nature of this odd effect remains unexplored. The purpose of this study is to reproduce a hypothetical molecular network recruited by caffeine when co-administered with zolpidem using Ingenuity Pathway Analysis. Thus generated, network drew attention to several possible contributors to caffeine sedation, such as tachykinin precursor 1, cannabinoid, and GABA receptors. The present overview is centered on the possibility that caffeine potentiation of zolpidem sedation does not involve a centralized interaction of specific neurotransmitters, but rather is contributed by its antioxidant capacity. It is proposed that by modifying the cellular redox state, caffeine ultimately reduces the pool of reactive oxygen species, thereby increasing the bioavailability of endogenous melatonin for interaction with zolpidem. This side effect of caffeine encourages further studies of multiple antioxidants as an attractive way to potentially increasing somnolence.

  6. Prediction of Narcissism, Perception of Social Interactions and Marital Conflicts Based on the Use of Social Networks

    Directory of Open Access Journals (Sweden)

    رویا رضاپور

    2017-09-01

    Full Text Available The prevalence of social networks and the excessive use of them by couples have had a significant impact on various aspects of their lives. The aim of this study was to investigate the role of social networks in the formation of narcissism, perception of social interaction and marital conflicts in couples who use these social networks. The study design was correlational and the statistical population included couples of Zanjan city who use social networks. 120 couples which widely used social networks were selected by random sampling. The questionnaires of Internet Addiction (Young, 1998, Narcissistic Personality (Ames and et al, 2006, Perception of Social Interaction (Glass, 1994 and Marital Conflict (Sanaei, 2000 were used. Pearson correlation coefficient and Regression were used for data analysis. This study showed that there is a significant negative relationship between the use of social networks with perception of social interaction, and a significant positive relationship between the use of social networks with narcissism and marital conflicts (P<0/01. Also narcissism has a significant positive relationship with marital conflicts, and a significant negative relationship with perception of social interaction (P<0/01. Social networks have a negative effect on couple's relationship and their feelings towards each other, as well as strengthening narcissism, which can cause communication problems, decreased positive feelings of couples towards each other and marital conflicts.

  7. Protein complex prediction in large ontology attributed protein-protein interaction networks.

    Science.gov (United States)

    Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Li, Yanpeng; Xu, Bo

    2013-01-01

    Protein complexes are important for unraveling the secrets of cellular organization and function. Many computational approaches have been developed to predict protein complexes in protein-protein interaction (PPI) networks. However, most existing approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology (GO) annotation information. In this paper, we constructed ontology attributed PPI networks with PPI data and GO resource. After constructing ontology attributed networks, we proposed a novel approach called CSO (clustering based on network structure and ontology attribute similarity). Structural information and GO attribute information are complementary in ontology attributed networks. CSO can effectively take advantage of the correlation between frequent GO annotation sets and the dense subgraph for protein complex prediction. Our proposed CSO approach was applied to four different yeast PPI data sets and predicted many well-known protein complexes. The experimental results showed that CSO was valuable in predicting protein complexes and achieved state-of-the-art performance.

  8. Skill Formation and Utilisation in the Post-Soviet Transition: Higher Education Planning in Post-Soviet Georgia

    Science.gov (United States)

    Gvaramadze, Irakli

    2010-01-01

    Changes in the former Soviet system had a dramatic influence on higher education in Georgia. The main objective of the current article is to analyse implications of the post-Soviet transition for the skill formation and skill utilisation system in Georgia. In particular, the study analyses recent trends in Georgian higher education including…

  9. Mental health and social networks in early adolescence: a dynamic study of objectively-measured social interaction behaviors.

    Science.gov (United States)

    Pachucki, Mark C; Ozer, Emily J; Barrat, Alain; Cattuto, Ciro

    2015-01-01

    How are social interaction dynamics associated with mental health during early stages of adolescence? The goal of this study is to objectively measure social interactions and evaluate the roles that multiple aspects of the social environment--such as physical activity and food choice--may jointly play in shaping the structure of children's relationships and their mental health. The data in this study are drawn from a longitudinal network-behavior study conducted in 2012 at a private K-8 school in an urban setting in California. We recruited a highly complete network sample of sixth-graders (n = 40, 91% of grade, mean age = 12.3), and examined how two measures of distressed mental health (self-esteem and depressive symptoms) are positionally distributed in an early adolescent interaction network. We ascertained how distressed mental health shapes the structure of relationships over a three-month period, adjusting for relevant dimensions of the social environment. Cross-sectional analyses of interaction networks revealed that self-esteem and depressive symptoms are differentially stratified by gender. Specifically, girls with more depressive symptoms have interactions consistent with social inhibition, while boys' interactions suggest robustness to depressive symptoms. Girls higher in self-esteem tended towards greater sociability. Longitudinal network behavior models indicate that gender similarity and perceived popularity are influential in the formation of social ties. Greater school connectedness predicts the development of self-esteem, though social ties contribute to more self-esteem improvement among students who identify as European-American. Cross-sectional evidence shows associations between distressed mental health and students' network peers. However, there is no evidence that connected students' mental health status becomes more similar in their over time because of their network interactions. These findings suggest that mental health during early

  10. Analysis of context dependence in social interaction networks of a massively multiplayer online role-playing game.

    Science.gov (United States)

    Son, Seokshin; Kang, Ah Reum; Kim, Hyun-chul; Kwon, Taekyoung; Park, Juyong; Kim, Huy Kang

    2012-01-01

    Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (MMORPGs), here we present a network science-based analysis of the interplay between distinct types of user interaction networks in the virtual world. We find that their properties depend critically on the nature of the context-interdependence of the interactions, highlighting the complex and multilayered nature of human interactions, a robust understanding of which we believe may prove instrumental in the designing of more realistic future virtual arenas as well as provide novel insights to the science of collective human behavior.

  11. Robust collaborative process interactions under system crash and network failures

    NARCIS (Netherlands)

    Wang, Lei; Wombacher, Andreas; Ferreira Pires, Luis; van Sinderen, Marten J.; Chi, Chihung

    2013-01-01

    With the possibility of system crashes and network failures, the design of robust client/server interactions for collaborative process execution is a challenge. If a business process changes its state, it sends messages to the relevant processes to inform about this change. However, server crashes

  12. Establishing Network Interaction between Resource Training Centers for People with Disabilities and Partner Universities

    Directory of Open Access Journals (Sweden)

    Panyukova S.V.,

    2018-05-01

    Full Text Available The paper focuses on the problem of accessibility and quality of higher education for students with disabilities. We describe our experience in organising network interaction between the MSUPE Resource and Training Center for Disabled People established in 2016-2017 and partner universities in ‘fixed territories’. The need for cooperation and network interaction arises from the high demand for the cooperation of efforts of leading experts, researchers, methodologists and instructors necessary for improving the quality and accessibility of higher education for persons with disabilities. The Resource and Training Center offers counseling for the partner universities, arranges advanced training for those responsible for teaching of the disabled, and offers specialized equipment for temporary use. In this article, we emphasize the importance of organizing network interactions with universities and social partners in order to ensure accessibility of higher education for students with disabilities.

  13. Interaction of chimera states in a multilayered network of nonlocally coupled oscillators

    Science.gov (United States)

    Goremyko, M. V.; Maksimenko, V. A.; Makarov, V. V.; Ghosh, D.; Bera, B.; Dana, S. K.; Hramov, A. E.

    2017-08-01

    The processes of formation and evolution of chimera states in the model of a multilayered network of nonlinear elements with complex coupling topology are studied. A two-layered network of nonlocally intralayer-coupled Kuramoto-Sakaguchi phase oscillators is taken as the object of investigation. Different modes implemented in this system upon variation of the degree of interlayer interaction are demonstrated.

  14. The attitude to nuclear energy in Georgia

    International Nuclear Information System (INIS)

    Saralidze, Z.

    2000-01-01

    Georgia, as a new independent state, is facing new problems regarding energy sources in the conditions of market economy. Great attention is given by the Government to search for various ways and versions to overcome the energy crisis. While nuclear energy may be an option for some reasons detailed in the paper, a nuclear power plant is not officially considered as an alternative. (author)

  15. Species interactions in an Andean bird–flowering plant network: phenology is more important than abundance or morphology

    Directory of Open Access Journals (Sweden)

    Oscar Gonzalez

    2016-12-01

    Full Text Available Biological constraints and neutral processes have been proposed to explain the properties of plant–pollinator networks. Using interactions between nectarivorous birds (hummingbirds and flowerpiercers and flowering plants in high elevation forests (i.e., “elfin” forests of the Andes, we explore the importance of biological constraints and neutral processes (random interactions to explain the observed species interactions and network metrics, such as connectance, specialization, nestedness and asymmetry. In cold environments of elfin forests, which are located at the top of the tropical montane forest zone, many plants are adapted for pollination by birds, making this an ideal system to study plant–pollinator networks. To build the network of interactions between birds and plants, we used direct field observations. We measured abundance of birds using mist-nets and flower abundance using transects, and phenology by scoring presence of birds and flowers over time. We compared the length of birds’ bills to flower length to identify “forbidden interactions”—those interactions that could not result in legitimate floral visits based on mis-match in morphology. Diglossa flowerpiercers, which are characterized as “illegitimate” flower visitors, were relatively abundant. We found that the elfin forest network was nested with phenology being the factor that best explained interaction frequencies and nestedness, providing support for biological constraints hypothesis. We did not find morphological constraints to be important in explaining observed interaction frequencies and network metrics. Other network metrics (connectance, evenness and asymmetry, however, were better predicted by abundance (neutral process models. Flowerpiercers, which cut holes and access flowers at their base and, consequently, facilitate nectar access for other hummingbirds, explain why morphological mis-matches were relatively unimportant in this system. Future

  16. Effects of watershed land use and geomorphology on stream low flows during severe drought conditions in the southern Blue Ridge Mountains, Georgia and North Carolina, United States

    Science.gov (United States)

    Katie Price; C. Jackson; Albert Parker; Trond Reitan; John Dowd; Mike Cyterski

    2011-01-01

    Land use and physiographic variability influence stream low flows, yet their interactions and relative influence remain unresolved. Our objective was to assess the influence of land use and watershed geomorphic characteristics on low-flow variability in the southern Blue Ridge Mountains of North Carolina and Georgia. Ten minute interval discharge data for 35 streams (...

  17. KNOWNET: Exploring Interactive Knowledge Networking across Insurance Supply Chains

    Directory of Open Access Journals (Sweden)

    Susan Grant

    2014-01-01

    Full Text Available Social media has become an extremely powerful phenomenon with millions of users who post status updates, blog, links and pictures on social networking sites such as Facebook, LinkedIn, and Twitter. However, social networking has so far spread mainly among consumers. Businesses are only now beginning to acknowledge the benefits of using social media to enhance employee and supplier collaboration to support new ideas and innovation through knowledge sharing across functions and organizational boundaries. Many businesses are still trying to understand the various implications of integrating internal communication systems with social media tools and private collaboration and networking platforms. Indeed, a current issue in organizations today is to explore the value of social media mechanisms across a range of functions within their organizations and across their supply chains.The KNOWNET project (an EC funded Marie Curie IAPP seeks to assess the value of social networking for knowledge exchange across Insurance supply chains. A key objective of the project being to develop and build a web based interactive environment - a Supplier Social Network or SSN, to support and facilitate exchange of good ideas, insights, knowledge, innovations etc across a diverse group of suppliers within a multi level supply chain within the Insurance sector.

  18. Georgia Teachers in Academic Laboratories: Research Experiences in the Geosciences

    Science.gov (United States)

    Barrett, D.

    2005-12-01

    The Georgia Intern-Fellowships for Teachers (GIFT) is a collaborative effort designed to enhance mathematics and science experiences of Georgia teachers and their students through summer research internships for teachers. By offering business, industry, public science institute and research summer fellowships to teachers, GIFT provides educators with first-hand exposure to the skills and knowledge necessary for the preparation of our future workforce. Since 1991, GIFT has placed middle and high school mathematics, science and technology teachers in over 1000 positions throughout the state. In these fellowships, teachers are involved in cutting edge scientific and engineering research, data analysis, curriculum development and real-world inquiry and problem solving, and create Action Plans to assist them in translating the experience into changed classroom practice. Since 2004, an increasing number of high school students have worked with their teachers in research laboratories. The GIFT program places an average of 75 teachers per summer into internship positions. In the summer of 2005, 83 teachers worked in corporate and research environments throughout the state of Georgia and six of these positions involved authentic research in geoscience related departments at the Georgia Institute of Technology, including aerospace engineering and the earth and atmospheric sciences laboratories. This presentation will review the history and the structure of the program including the support system for teachers and mentors as well as the emphasis on inquiry based learning strategies. The focus of the presentation will be a comparison of two placement models of the teachers placed in geoscience research laboratories: middle school earth science teachers placed in a 6 week research experience and high school teachers placed in 7 week internships with teams of 3 high school students. The presentation will include interviews with faculty to determine the value of these experiences

  19. Seroepidemiology and molecular diversity of Leishmania donovani complex in Georgia.

    Science.gov (United States)

    Babuadze, Giorgi; Farlow, Jason; de Koning, Harry P; Carrillo, Eugenia; Chakhunashvili, Giorgi; Murskvaladze, Mari; Kekelidze, Merab; Karseladze, Irakli; Kokaia, Nora; Kalandadze, Irine; Tsereteli, David; Markhvashvili, Ivane; Sidamonidze, Ketevan; Chanturia, Gvantsa; Adeishvili, Ekaterine; Imnadze, Paata

    2016-05-13

    Leishmaniasis includes multiple clinical syndromes, most notably visceral, cutaneous, and mucosal forms. Visceral leishmaniasis (VL), also known as kala-azar, is a potentially fatal disease endemic to large parts of Africa and Asia, and in South-Eastern Europe (Greece, Turkey, Georgia). Visceral leishmaniasis is a parasitic zoonosis caused by species of the L. donovani complex. In the classical epidemiological model the main reservoir for VL are canines. The study included a cohort of 513 individuals of both genders (190 males and 323 females) from the ages of 1 to 70 years that were screened in ten villages across two districts in Kakheti using the Kalazar Detect™ rK39 rapid diagnostic test. The phylogenetic diversity patterns of local strains, based on the rDNA internal transcribed spacer (ITS) sequences, were assessed for samples obtained from patients with suspected L. donovani infection, from canine reservoirs and from Phlebotomus sand flies obtained from different geographical areas of Georgia and from Azerbaijan. Out of a total of 600 domestic dog blood samples 95 (15.8 %) were positive by rK39 rapid diagnostic tests. For symptomatic domestic dogs, the testing of conjunctival swabs or bone marrow aspirates revealed a higher VL incidence in Kvareli District (Kvareli; 19.4 %, n = 329) compared with that observed for Sagarejo District (Sagarejo; 11.4 %, n = 271). A total of 231 sand flies of both genders were collected during the 2-month period; of the 114 females, 1.75 % were PCR positive for the presence of Leishmania spp. VL infection rates remain high in both canines and humans in Georgia, with disease in several known natural foci. The genetic relationships derived from rDNA internal transcribed spacer (ITS) sequence comparisons identified genetic subgroups, revealing preliminary insights into the genetic structure of L. donovani complex members currently circulating in the South Caucasus and demonstrates the utility of ITS-based genotyping

  20. P-Finder: Reconstruction of Signaling Networks from Protein-Protein Interactions and GO Annotations.

    Science.gov (United States)

    Young-Rae Cho; Yanan Xin; Speegle, Greg

    2015-01-01

    Because most complex genetic diseases are caused by defects of cell signaling, illuminating a signaling cascade is essential for understanding their mechanisms. We present three novel computational algorithms to reconstruct signaling networks between a starting protein and an ending protein using genome-wide protein-protein interaction (PPI) networks and gene ontology (GO) annotation data. A signaling network is represented as a directed acyclic graph in a merged form of multiple linear pathways. An advanced semantic similarity metric is applied for weighting PPIs as the preprocessing of all three methods. The first algorithm repeatedly extends the list of nodes based on path frequency towards an ending protein. The second algorithm repeatedly appends edges based on the occurrence of network motifs which indicate the link patterns more frequently appearing in a PPI network than in a random graph. The last algorithm uses the information propagation technique which iteratively updates edge orientations based on the path strength and merges the selected directed edges. Our experimental results demonstrate that the proposed algorithms achieve higher accuracy than previous methods when they are tested on well-studied pathways of S. cerevisiae. Furthermore, we introduce an interactive web application tool, called P-Finder, to visualize reconstructed signaling networks.

  1. Prostate cancer incidence and tumor severity in Georgia: descriptive epidemiology, racial disparity, and geographic trends.

    Science.gov (United States)

    Wagner, Sara E; Bauer, Sarah E; Bayakly, A Rana; Vena, John E

    2013-01-01

    Limited research has been conducted to describe the geographical clustering and distribution of prostate cancer (PrCA) incidence in Georgia (GA). This study describes and compares the temporal and geographic trends of PrCA incidence in GA with a specific focus on racial disparities. GA Comprehensive Cancer Registry PrCA incidence data were obtained for 1998-2008. Directly standardized age-adjusted PrCA incidence rates per 100,000 were analyzed by race, stage, grade, and county. County-level hotspots of PrCA incidence were analyzed with the Getis-Ord Gi* statistic in a geographic information system; a census tract-level cluster analysis was performed with a Discrete Poisson model and implemented in SaTScan(®) software. Significant (p incidence were observed in nine southwestern counties and six centrally located counties among men of both races. Six significant (p incidence rates were detected for men of both races in north and northwest central Georgia. When stratified by race, clusters among white and black men were similar, although centroids were slightly shifted. Most notably, a large (122 km radius) cluster in northwest central Georgia was detected only in whites, and two smaller clusters (0-32 km radii) were detected in Southwest Georgia only in black men. Clusters of high-grade and late-stage tumors were identified primarily in the northern portion of the state among men of both races. This study revealed a pattern of higher incidence and more advanced disease in northern and northwest central Georgia, highlighting geographic patterns that need more research and investigation of possible environmental determinants.

  2. Dynamics of person-to-person interactions from distributed RFID sensor networks.

    Directory of Open Access Journals (Sweden)

    Ciro Cattuto

    Full Text Available BACKGROUND: Digital networks, mobile devices, and the possibility of mining the ever-increasing amount of digital traces that we leave behind in our daily activities are changing the way we can approach the study of human and social interactions. Large-scale datasets, however, are mostly available for collective and statistical behaviors, at coarse granularities, while high-resolution data on person-to-person interactions are generally limited to relatively small groups of individuals. Here we present a scalable experimental framework for gathering real-time data resolving face-to-face social interactions with tunable spatial and temporal granularities. METHODS AND FINDINGS: We use active Radio Frequency Identification (RFID devices that assess mutual proximity in a distributed fashion by exchanging low-power radio packets. We analyze the dynamics of person-to-person interaction networks obtained in three high-resolution experiments carried out at different orders of magnitude in community size. The data sets exhibit common statistical properties and lack of a characteristic time scale from 20 seconds to several hours. The association between the number of connections and their duration shows an interesting super-linear behavior, which indicates the possibility of defining super-connectors both in the number and intensity of connections. CONCLUSIONS: Taking advantage of scalability and resolution, this experimental framework allows the monitoring of social interactions, uncovering similarities in the way individuals interact in different contexts, and identifying patterns of super-connector behavior in the community. These results could impact our understanding of all phenomena driven by face-to-face interactions, such as the spreading of transmissible infectious diseases and information.

  3. Tolerance-based interaction: a new model targeting opinion formation and diffusion in social networks

    Directory of Open Access Journals (Sweden)

    Alexandru Topirceanu

    2016-01-01

    Full Text Available One of the main motivations behind social network analysis is the quest for understanding opinion formation and diffusion. Previous models have limitations, as they typically assume opinion interaction mechanisms based on thresholds which are either fixed or evolve according to a random process that is external to the social agent. Indeed, our empirical analysis on large real-world datasets such as Twitter, Meme Tracker, and Yelp, uncovers previously unaccounted for dynamic phenomena at population-level, namely the existence of distinct opinion formation phases and social balancing. We also reveal that a phase transition from an erratic behavior to social balancing can be triggered by network topology and by the ratio of opinion sources. Consequently, in order to build a model that properly accounts for these phenomena, we propose a new (individual-level opinion interaction model based on tolerance. As opposed to the existing opinion interaction models, the new tolerance model assumes that individual’s inner willingness to accept new opinions evolves over time according to basic human traits. Finally, by employing discrete event simulation on diverse social network topologies, we validate our opinion interaction model and show that, although the network size and opinion source ratio are important, the phase transition to social balancing is mainly fostered by the democratic structure of the small-world topology.

  4. Data on overlapping brain disorders and emerging drug targets in human Dopamine Receptors Interaction Network

    Directory of Open Access Journals (Sweden)

    Avijit Podder

    2017-06-01

    Full Text Available Intercommunication of Dopamine Receptors (DRs with their associate protein partners is crucial to maintain regular brain function in human. Majority of the brain disorders arise due to malfunctioning of such communication process. Hence, contributions of genetic factors, as well as phenotypic indications for various neurological and psychiatric disorders are often attributed as sharing in nature. In our earlier research article entitled “Human Dopamine Receptors Interaction Network (DRIN: a systems biology perspective on topology, stability and functionality of the network” (Podder et al., 2014 [1], we had depicted a holistic interaction map of human Dopamine Receptors. Given emphasis on the topological parameters, we had characterized the functionality along with the vulnerable properties of the network. In support of this, we hereby provide an additional data highlighting the genetic overlapping of various brain disorders in the network. The data indicates the sharing nature of disease genes for various neurological and psychiatric disorders in dopamine receptors connecting protein-protein interactions network. The data also indicates toward an alternative approach to prioritize proteins for overlapping brain disorders as valuable drug targets in the network.

  5. Using the clustered circular layout as an informative method for visualizing protein-protein interaction networks.

    Science.gov (United States)

    Fung, David C Y; Wilkins, Marc R; Hart, David; Hong, Seok-Hee

    2010-07-01

    The force-directed layout is commonly used in computer-generated visualizations of protein-protein interaction networks. While it is good for providing a visual outline of the protein complexes and their interactions, it has two limitations when used as a visual analysis method. The first is poor reproducibility. Repeated running of the algorithm does not necessarily generate the same layout, therefore, demanding cognitive readaptation on the investigator's part. The second limitation is that it does not explicitly display complementary biological information, e.g. Gene Ontology, other than the protein names or gene symbols. Here, we present an alternative layout called the clustered circular layout. Using the human DNA replication protein-protein interaction network as a case study, we compared the two network layouts for their merits and limitations in supporting visual analysis.

  6. Potato leafroll virus structural proteins manipulate overlapping, yet distinct protein interaction networks during infection.

    Science.gov (United States)

    DeBlasio, Stacy L; Johnson, Richard; Sweeney, Michelle M; Karasev, Alexander; Gray, Stewart M; MacCoss, Michael J; Cilia, Michelle

    2015-06-01

    Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a nonincorporated protein in concert with numerous insect and plant proteins to regulate virus movement/transmission and tissue tropism. Affinity purification coupled to quantitative MS was used to generate protein interaction networks for a PLRV mutant that is unable to produce the read through domain (RTD) and compared to the known wild-type PLRV protein interaction network. By quantifying differences in the protein interaction networks, we identified four distinct classes of PLRV-plant interactions: those plant and nonstructural viral proteins interacting with assembled coat protein (category I); plant proteins in complex with both coat protein and RTD (category II); plant proteins in complex with the RTD (category III); and plant proteins that had higher affinity for virions lacking the RTD (category IV). Proteins identified as interacting with the RTD are potential candidates for regulating viral processes that are mediated by the RTP such as phloem retention and systemic movement and can potentially be useful targets for the development of strategies to prevent infection and/or viral transmission of Luteoviridae species that infect important crop species. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. The Effect of Social Interaction on Learning Engagement in a Social Networking Environment

    Science.gov (United States)

    Lu, Jie; Churchill, Daniel

    2014-01-01

    This study investigated the impact of social interactions among a class of undergraduate students on their learning engagement in a social networking environment. Thirteen undergraduate students enrolled in a course in a university in Hong Kong used an Elgg-based social networking platform throughout a semester to develop their digital portfolios…

  8. Insight into bacterial virulence mechanisms against host immune response via the Yersinia pestis-human protein-protein interaction network.

    Science.gov (United States)

    Yang, Huiying; Ke, Yuehua; Wang, Jian; Tan, Yafang; Myeni, Sebenzile K; Li, Dong; Shi, Qinghai; Yan, Yanfeng; Chen, Hui; Guo, Zhaobiao; Yuan, Yanzhi; Yang, Xiaoming; Yang, Ruifu; Du, Zongmin

    2011-11-01

    A Yersinia pestis-human protein interaction network is reported here to improve our understanding of its pathogenesis. Up to 204 interactions between 66 Y. pestis bait proteins and 109 human proteins were identified by yeast two-hybrid assay and then combined with 23 previously published interactions to construct a protein-protein interaction network. Topological analysis of the interaction network revealed that human proteins targeted by Y. pestis were significantly enriched in the proteins that are central in the human protein-protein interaction network. Analysis of this network showed that signaling pathways important for host immune responses were preferentially targeted by Y. pestis, including the pathways involved in focal adhesion, regulation of cytoskeleton, leukocyte transendoepithelial migration, and Toll-like receptor (TLR) and mitogen-activated protein kinase (MAPK) signaling. Cellular pathways targeted by Y. pestis are highly relevant to its pathogenesis. Interactions with host proteins involved in focal adhesion and cytoskeketon regulation pathways could account for resistance of Y. pestis to phagocytosis. Interference with TLR and MAPK signaling pathways by Y. pestis reflects common characteristics of pathogen-host interaction that bacterial pathogens have evolved to evade host innate immune response by interacting with proteins in those signaling pathways. Interestingly, a large portion of human proteins interacting with Y. pestis (16/109) also interacted with viral proteins (Epstein-Barr virus [EBV] and hepatitis C virus [HCV]), suggesting that viral and bacterial pathogens attack common cellular functions to facilitate infections. In addition, we identified vasodilator-stimulated phosphoprotein (VASP) as a novel interaction partner of YpkA and showed that YpkA could inhibit in vitro actin assembly mediated by VASP.

  9. Protein complex prediction based on k-connected subgraphs in protein interaction network

    OpenAIRE

    Habibi, Mahnaz; Eslahchi, Changiz; Wong, Limsoon

    2010-01-01

    Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on ...

  10. Complete Neuron-Astrocyte Interaction Model: Digital Multiplierless Design and Networking Mechanism.

    Science.gov (United States)

    Haghiri, Saeed; Ahmadi, Arash; Saif, Mehrdad

    2017-02-01

    Glial cells, also known as neuroglia or glia, are non-neuronal cells providing support and protection for neurons in the central nervous system (CNS). They also act as supportive cells in the brain. Among a variety of glial cells, the star-shaped glial cells, i.e., astrocytes, are the largest cell population in the brain. The important role of astrocyte such as neuronal synchronization, synaptic information regulation, feedback to neural activity and extracellular regulation make the astrocytes play a vital role in brain disease. This paper presents a modified complete neuron-astrocyte interaction model that is more suitable for efficient and large scale biological neural network realization on digital platforms. Simulation results show that the modified complete interaction model can reproduce biological-like behavior of the original neuron-astrocyte mechanism. The modified interaction model is investigated in terms of digital realization feasibility and cost targeting a low cost hardware implementation. Networking behavior of this interaction is investigated and compared between two cases: i) the neuron spiking mechanism without astrocyte effects, and ii) the effect of astrocyte in regulating the neurons behavior and synaptic transmission via controlling the LTP and LTD processes. Hardware implementation on FPGA shows that the modified model mimics the main mechanism of neuron-astrocyte communication with higher performance and considerably lower hardware overhead cost compared with the original interaction model.

  11. The human-bacterial pathogen protein interaction networks of Bacillus anthracis, Francisella tularensis, and Yersinia pestis.

    Directory of Open Access Journals (Sweden)

    Matthew D Dyer

    2010-08-01

    Full Text Available Bacillus anthracis, Francisella tularensis, and Yersinia pestis are bacterial pathogens that can cause anthrax, lethal acute pneumonic disease, and bubonic plague, respectively, and are listed as NIAID Category A priority pathogens for possible use as biological weapons. However, the interactions between human proteins and proteins in these bacteria remain poorly characterized leading to an incomplete understanding of their pathogenesis and mechanisms of immune evasion.In this study, we used a high-throughput yeast two-hybrid assay to identify physical interactions between human proteins and proteins from each of these three pathogens. From more than 250,000 screens performed, we identified 3,073 human-B. anthracis, 1,383 human-F. tularensis, and 4,059 human-Y. pestis protein-protein interactions including interactions involving 304 B. anthracis, 52 F. tularensis, and 330 Y. pestis proteins that are uncharacterized. Computational analysis revealed that pathogen proteins preferentially interact with human proteins that are hubs and bottlenecks in the human PPI network. In addition, we computed modules of human-pathogen PPIs that are conserved amongst the three networks. Functionally, such conserved modules reveal commonalities between how the different pathogens interact with crucial host pathways involved in inflammation and immunity.These data constitute the first extensive protein interaction networks constructed for bacterial pathogens and their human hosts. This study provides novel insights into host-pathogen interactions.

  12. Automation and Its Funding in the Library Media Centers in Secondary Schools in Georgia: A Survey.

    Science.gov (United States)

    Baggett, Ann Utsey

    This report presents the results of a study whose purpose was to determine what automation is present in the library media centers in Georgia secondary schools and how it has been funded. A three-part questionnaire was sent to the media specialists in 50% of the secondary schools in Georgia, which were randomly selected. The analysis of the…

  13. Analysis of Context Dependence in Social Interaction Networks of a Massively Multiplayer Online Role-Playing Game

    Science.gov (United States)

    Son, Seokshin; Kang, Ah Reum; Kim, Hyun-chul; Kwon, Taekyoung; Park, Juyong; Kim, Huy Kang

    2012-01-01

    Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (MMORPGs), here we present a network science-based analysis of the interplay between distinct types of user interaction networks in the virtual world. We find that their properties depend critically on the nature of the context-interdependence of the interactions, highlighting the complex and multilayered nature of human interactions, a robust understanding of which we believe may prove instrumental in the designing of more realistic future virtual arenas as well as provide novel insights to the science of collective human behavior. PMID:22496771

  14. Analysis of context dependence in social interaction networks of a massively multiplayer online role-playing game.

    Directory of Open Access Journals (Sweden)

    Seokshin Son

    Full Text Available Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (MMORPGs, here we present a network science-based analysis of the interplay between distinct types of user interaction networks in the virtual world. We find that their properties depend critically on the nature of the context-interdependence of the interactions, highlighting the complex and multilayered nature of human interactions, a robust understanding of which we believe may prove instrumental in the designing of more realistic future virtual arenas as well as provide novel insights to the science of collective human behavior.

  15. Georgia Health - Go Local: Using Multidisciplinary Partnerships to Promote a Statewide Consumer Health Website.

    Science.gov (United States)

    Smith, Rita B

    2011-01-01

    The National Library of Medicine ended its support of the Go Local program in 2010 due to declining usage, but in many ways Georgia's project was a success. From its beginning, Georgia Health - Go Local was a model of successful collaboration among a variety of partners and institutions throughout the state. The high usage statistics for the Go Local website and the support garnered by the project exemplify the positive nature of the collaborations that made the project possible.

  16. The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature.

    Science.gov (United States)

    Özgür, Arzucan; Hur, Junguk; He, Yongqun

    2016-01-01

    The Interaction Network Ontology (INO) logically represents biological interactions, pathways, and networks. INO has been demonstrated to be valuable in providing a set of structured ontological terms and associated keywords to support literature mining of gene-gene interactions from biomedical literature. However, previous work using INO focused on single keyword matching, while many interactions are represented with two or more interaction keywords used in combination. This paper reports our extension of INO to include combinatory patterns of two or more literature mining keywords co-existing in one sentence to represent specific INO interaction classes. Such keyword combinations and related INO interaction type information could be automatically obtained via SPARQL queries, formatted in Excel format, and used in an INO-supported SciMiner, an in-house literature mining program. We studied the gene interaction sentences from the commonly used benchmark Learning Logic in Language (LLL) dataset and one internally generated vaccine-related dataset to identify and analyze interaction types containing multiple keywords. Patterns obtained from the dependency parse trees of the sentences were used to identify the interaction keywords that are related to each other and collectively represent an interaction type. The INO ontology currently has 575 terms including 202 terms under the interaction branch. The relations between the INO interaction types and associated keywords are represented using the INO annotation relations: 'has literature mining keywords' and 'has keyword dependency pattern'. The keyword dependency patterns were generated via running the Stanford Parser to obtain dependency relation types. Out of the 107 interactions in the LLL dataset represented with two-keyword interaction types, 86 were identified by using the direct dependency relations. The LLL dataset contained 34 gene regulation interaction types, each of which associated with multiple keywords. A

  17. Improving functional modules discovery by enriching interaction networks with gene profiles

    KAUST Repository

    Salem, Saeed; Alroobi, Rami; Banitaan, Shadi; Seridi, Loqmane; Aljarah, Ibrahim; Brewer, James

    2013-01-01

    networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional

  18. When the Web meets the cell: using personalized PageRank for analyzing protein interaction networks.

    Science.gov (United States)

    Iván, Gábor; Grolmusz, Vince

    2011-02-01

    Enormous and constantly increasing quantity of biological information is represented in metabolic and in protein interaction network databases. Most of these data are freely accessible through large public depositories. The robust analysis of these resources needs novel technologies, being developed today. Here we demonstrate a technique, originating from the PageRank computation for the World Wide Web, for analyzing large interaction networks. The method is fast, scalable and robust, and its capabilities are demonstrated on metabolic network data of the tuberculosis bacterium and the proteomics analysis of the blood of melanoma patients. The Perl script for computing the personalized PageRank in protein networks is available for non-profit research applications (together with sample input files) at the address: http://uratim.com/pp.zip.

  19. Topological and organizational properties of the products of house-keeping and tissue-specific genes in protein-protein interaction networks.

    Science.gov (United States)

    Lin, Wen-Hsien; Liu, Wei-Chung; Hwang, Ming-Jing

    2009-03-11

    Human cells of various tissue types differ greatly in morphology despite having the same set of genetic information. Some genes are expressed in all cell types to perform house-keeping functions, while some are selectively expressed to perform tissue-specific functions. In this study, we wished to elucidate how proteins encoded by human house-keeping genes and tissue-specific genes are organized in human protein-protein interaction networks. We constructed protein-protein interaction networks for different tissue types using two gene expression datasets and one protein-protein interaction database. We then calculated three network indices of topological importance, the degree, closeness, and betweenness centralities, to measure the network position of proteins encoded by house-keeping and tissue-specific genes, and quantified their local connectivity structure. Compared to a random selection of proteins, house-keeping gene-encoded proteins tended to have a greater number of directly interacting neighbors and occupy network positions in several shortest paths of interaction between protein pairs, whereas tissue-specific gene-encoded proteins did not. In addition, house-keeping gene-encoded proteins tended to connect with other house-keeping gene-encoded proteins in all tissue types, whereas tissue-specific gene-encoded proteins also tended to connect with other tissue-specific gene-encoded proteins, but only in approximately half of the tissue types examined. Our analysis showed that house-keeping gene-encoded proteins tend to occupy important network positions, while those encoded by tissue-specific genes do not. The biological implications of our findings were discussed and we proposed a hypothesis regarding how cells organize their protein tools in protein-protein interaction networks. Our results led us to speculate that house-keeping gene-encoded proteins might form a core in human protein-protein interaction networks, while clusters of tissue-specific gene

  20. ITS/CVO strategic & business plan for the state of Georgia

    Science.gov (United States)

    1998-05-01

    This document records the State of Georgias strategic and tactical plans for employing ITS/CVO technology to improve its Commercial Vehicle Administration (CVA) functions. The process by which this plan was developed included a detailed assessment...

  1. Exploring drug-target interaction networks of illicit drugs.

    Science.gov (United States)

    Atreya, Ravi V; Sun, Jingchun; Zhao, Zhongming

    2013-01-01

    Drug addiction is a complex and chronic mental disease, which places a large burden on the American healthcare system due to its negative effects on patients and their families. Recently, network pharmacology is emerging as a promising approach to drug discovery by integrating network biology and polypharmacology, allowing for a deeper understanding of molecular mechanisms of drug actions at the systems level. This study seeks to apply this approach for investigation of illicit drugs and their targets in order to elucidate their interaction patterns and potential secondary drugs that can aid future research and clinical care. In this study, we extracted 188 illicit substances and their related information from the DrugBank database. The data process revealed 86 illicit drugs targeting a total of 73 unique human genes, which forms an illicit drug-target network. Compared to the full drug-target network from DrugBank, illicit drugs and their target genes tend to cluster together and form four subnetworks, corresponding to four major medication categories: depressants, stimulants, analgesics, and steroids. External analysis of Anatomical Therapeutic Chemical (ATC) second sublevel classifications confirmed that the illicit drugs have neurological functions or act via mechanisms of stimulants, opioids, and steroids. To further explore other drugs potentially having associations with illicit drugs, we constructed an illicit-extended drug-target network by adding the drugs that have the same target(s) as illicit drugs to the illicit drug-target network. After analyzing the degree and betweenness of the network, we identified hubs and bridge nodes, which might play important roles in the development and treatment of drug addiction. Among them, 49 non-illicit drugs might have potential to be used to treat addiction or have addictive effects, including some results that are supported by previous studies. This study presents the first systematic review of the network

  2. Global product development interaction between local networks: A study of the Danish food industry

    DEFF Research Database (Denmark)

    Kristensen, Preben Sander

    A study of the Danish foods industry shows that producers of food products largely ignore home marekt demand in their product development activities. They have built up and maintain development of end-user products in interaction with customers in distant sophisticated markets. Concurrently...... view of actors in the global end-user customer market and companies' euclidean view of actors in thelocal business-to-business market. In pr companies combine these two market views by interacting in networks: The global industrial network links various functions which again are each part of a local...... their development of end-user pr through global interaction. It is precisely by not interacting with home market end-user demand, but rather by deriving an industrial home market demand from changing end-user markets that the complex has avoided being insulated....

  3. First Vertical Land Movement Estimates on South Georgia Island: An Impact Study on Sea Level Change from Tide Gauge and Satellite Altimetry Measurements

    Science.gov (United States)

    Abraha, K. E.; Teferle, F. N.; Hunegnaw, A.; Woodworth, P. L.; Williams, S. D. P.; Hibbert, A.; Smalley, R., Jr.; Dalziel, I.; Lawver, L.

    2017-12-01

    South Georgia Island in the Southern Atlantic Ocean has been a key location for the seismic, geomagnetic and oceanic global monitoring networks. However, no permanent geodetic monitoring station had been established there despite the lack of observations from this region within, for example, the International GNSS Service (IGS) network of Global Navigation Satellite System (GNSS) stations. Then, in 2013 the King Edward Point (KEP) Geodetic Observatory was established with a focus on sea level studies and in support of general geoscience applications. Currently, this observatory located roughly half-way along the main island along its northern coastline, consists of two GNSS stations (KEPA and KRSA) with local benchmark networks, allowing the height determinations from the GNSS antennas to be transferred to the KEP tide gauge (GLOSS ID 187) and forming a height reference within the International Terrestrial Reference Frame. In late 2014, three additional GNSS stations (SG01, SG02 and SG03) were established, all located on small islands at the perimeter of the main island. Together the stations provide the best possible geographic distribution to study various geophysical processes in the region. With the GNSS-derived position time series now partly reaching over 4.5 years in length, it has become possible to provide first estimates of vertical land movements for the island and, in particular, KEP with its surrounding area. Together with four precise levelling campaigns of the benchmark network in 2013, 2014 and two in 2017, it has also been possible to investigate the very local character of the vertical motions, ie. the stability of the jetty upon which the tide gauge is mounted. Our measurements show that while South Georgia Island and the area around KEP are rising, the jetty and tide gauge are subsiding. In this study, we will present the preliminary results from the GNSS and levelling measurements and will discuss their impact on the sea level record from the

  4. Pierce - University of Georgia | Division of Cancer Prevention

    Science.gov (United States)

    Principal Investigator: J. Michael Pierce, PhDInstitution: University of Georgia, Athens, GA Our project, Discovery and Development of Cancer Glycomarkers, is a joint collaboration between our laboratories at the CCRC, which include Karen Abbott, Lance Wells, Kevin Dobbin, and Mike Tiemeyer, those at TGen, in Phoenix, AZ, Daniel Von Hoff, Haiyong Han, and Mike Demeure, and

  5. The patterns of organisation and structure of interactions in a fish-parasite network of a neotropical river.

    Science.gov (United States)

    Bellay, Sybelle; Oliveira, Edson F de; Almeida-Neto, Mário; Abdallah, Vanessa D; Azevedo, Rodney K de; Takemoto, Ricardo M; Luque, José L

    2015-07-01

    The use of the complex network approach to study host-parasite interactions has helped to improve the understanding of the structure and dynamics of ecological communities. In this study, this network approach is applied to evaluate the patterns of organisation and structure of interactions in a fish-parasite network of a neotropical Atlantic Forest river. The network includes 20 fish species and 73 metazoan parasite species collected from the Guandu River, Rio de Janeiro State, Brazil. According to the usual measures in studies of networks, the organisation of the network was evaluated using measures of host susceptibility, parasite dependence, interaction asymmetry, species strength and complementary specialisation of each species as well as the network. The network structure was evaluated using connectance, nestedness and modularity measures. Host susceptibility typically presented low values, whereas parasite dependence was high. The asymmetry and species strength were correlated with host taxonomy but not with parasite taxonomy. Differences among parasite taxonomic groups in the complementary specialisation of each species on hosts were also observed. However, the complementary specialisation and species strength values were not correlated. The network had a high complementary specialisation, low connectance and nestedness, and high modularity, thus indicating variability in the roles of species in the network organisation and the expected presence of many specialist species. Copyright © 2015 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

  6. The Seven-Year Plan of Georgia - USSR .

    Science.gov (United States)

    1961-08-07

    Georgian art. A new pleiad of talented singers, musicians and artists has appeared. At a review of the cultural achievements of Georgia held in Moscow...and gymnastics are favorite types of athletics. The creation of a sport base, of cadres of trainers and teachers makes it possible to train first...account the actual demands of industry. Writers and artists are concluding friendship treaties with enterprises and constructions* The initiative

  7. Uncovering packaging features of co-regulated modules based on human protein interaction and transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    He Weiming

    2010-07-01

    Full Text Available Abstract Background Network co-regulated modules are believed to have the functionality of packaging multiple biological entities, and can thus be assumed to coordinate many biological functions in their network neighbouring regions. Results Here, we weighted edges of a human protein interaction network and a transcriptional regulatory network to construct an integrated network, and introduce a probabilistic model and a bipartite graph framework to exploit human co-regulated modules and uncover their specific features in packaging different biological entities (genes, protein complexes or metabolic pathways. Finally, we identified 96 human co-regulated modules based on this method, and evaluate its effectiveness by comparing it with four other methods. Conclusions Dysfunctions in co-regulated interactions often occur in the development of cancer. Therefore, we focussed on an example co-regulated module and found that it could integrate a number of cancer-related genes. This was extended to causal dysfunctions of some complexes maintained by several physically interacting proteins, thus coordinating several metabolic pathways that directly underlie cancer.

  8. Interaction of multiple networks modulated by the working memory training based on real-time fMRI

    Science.gov (United States)

    Shen, Jiahui; Zhang, Gaoyan; Zhu, Chaozhe; Yao, Li; Zhao, Xiaojie

    2015-03-01

    Neuroimaging studies of working memory training have identified the alteration of brain activity as well as the regional interactions within the functional networks such as central executive network (CEN) and default mode network (DMN). However, how the interaction within and between these multiple networks is modulated by the training remains unclear. In this paper, we examined the interaction of three training-induced brain networks during working memory training based on real-time functional magnetic resonance imaging (rtfMRI). Thirty subjects assigned to the experimental and control group respectively participated in two times training separated by seven days. Three networks including silence network (SN), CEN and DMN were identified by the training data with the calculated function connections within each network. Structural equation modeling (SEM) approach was used to construct the directional connectivity patterns. The results showed that the causal influences from the percent signal changes of target ROI to the SN were positively changed in both two groups, as well as the causal influence from the SN to CEN was positively changed in experimental group but negatively changed in control group from the SN to DMN. Further correlation analysis of the changes in each network with the behavioral improvements showed that the changes in SN were stronger positively correlated with the behavioral improvement of letter memory task. These findings indicated that the SN was not only a switch between the target ROI and the other networks in the feedback training but also an essential factor to the behavioral improvement.

  9. The social fabric of elementary schools: a network typology of social interaction among teachers

    NARCIS (Netherlands)

    Moolenaar, N.M.; Sleegers, P.J.C.; Karsten, S.; Daly, A.J.

    2012-01-01

    While researchers are currently studying various forms of social network interaction among teachers for their impact on educational policy implementation and practice, knowledge on how various types of networks are interrelated is limited. The goal of this study is to understand the dimensionality

  10. The social fabric of elementary schools: A network typology of social interaction among teachers

    NARCIS (Netherlands)

    Moolenaar, Nienke; Sleegers, P.J.C.; Karsten, Sjoerd; Daly, Alan J.; Daly, A.J.

    2012-01-01

    While researchers are currently studying various forms of social network interaction among teachers for their impact on educational policy implementation and practice, knowledge on how various types of networks are interrelated is limited. The goal of this study is to understand the dimensionality

  11. Institutional and financial analysis of weigh station performance in Georgia.

    Science.gov (United States)

    2011-10-01

    This report examines the State of Georgias commercial vehicle oversize and overweight enforcement : program over the past 10 years. An overview of the federal and state regulations for both oversize and overweight : vehicles is presented, which in...

  12. Brain Interaction during Cooperation: Evaluating Local Properties of Multiple-Brain Network.

    Science.gov (United States)

    Sciaraffa, Nicolina; Borghini, Gianluca; Aricò, Pietro; Di Flumeri, Gianluca; Colosimo, Alfredo; Bezerianos, Anastasios; Thakor, Nitish V; Babiloni, Fabio

    2017-07-21

    Subjects' interaction is the core of most human activities. This is the reason why a lack of coordination is often the cause of missing goals, more than individual failure. While there are different subjective and objective measures to assess the level of mental effort required by subjects while facing a situation that is getting harder, that is, mental workload, to define an objective measure based on how and if team members are interacting is not so straightforward. In this study, behavioral, subjective and synchronized electroencephalographic data were collected from couples involved in a cooperative task to describe the relationship between task difficulty and team coordination, in the sense of interaction aimed at cooperatively performing the assignment. Multiple-brain connectivity analysis provided information about the whole interacting system. The results showed that averaged local properties of a brain network were affected by task difficulty. In particular, strength changed significantly with task difficulty and clustering coefficients strongly correlated with the workload itself. In particular, a higher workload corresponded to lower clustering values over the central and parietal brain areas. Such results has been interpreted as less efficient organization of the network when the subjects' activities, due to high workload tendencies, were less coordinated.

  13. Musical Imagery Involves Wernicke's Area in Bilateral and Anti-Correlated Network Interactions in Musicians.

    Science.gov (United States)

    Zhang, Yizhen; Chen, Gang; Wen, Haiguang; Lu, Kun-Han; Liu, Zhongming

    2017-12-06

    Musical imagery is the human experience of imagining music without actually hearing it. The neural basis of this mental ability is unclear, especially for musicians capable of engaging in accurate and vivid musical imagery. Here, we created a visualization of an 8-minute symphony as a silent movie and used it as real-time cue for musicians to continuously imagine the music for repeated and synchronized sessions during functional magnetic resonance imaging (fMRI). The activations and networks evoked by musical imagery were compared with those elicited by the subjects directly listening to the same music. Musical imagery and musical perception resulted in overlapping activations at the anterolateral belt and Wernicke's area, where the responses were correlated with the auditory features of the music. Whereas Wernicke's area interacted within the intrinsic auditory network during musical perception, it was involved in much more complex networks during musical imagery, showing positive correlations with the dorsal attention network and the motor-control network and negative correlations with the default-mode network. Our results highlight the important role of Wernicke's area in forming vivid musical imagery through bilateral and anti-correlated network interactions, challenging the conventional view of segregated and lateralized processing of music versus language.

  14. The robustness of pollination networks to the loss of species and interactions: a quantitative approach incorporating pollinator behaviour.

    Science.gov (United States)

    Kaiser-Bunbury, Christopher N; Muff, Stefanie; Memmott, Jane; Müller, Christine B; Caflisch, Amedeo

    2010-04-01

    Species extinctions pose serious threats to the functioning of ecological communities worldwide. We used two qualitative and quantitative pollination networks to simulate extinction patterns following three removal scenarios: random removal and systematic removal of the strongest and weakest interactors. We accounted for pollinator behaviour by including potential links into temporal snapshots (12 consecutive 2-week networks) to reflect mutualists' ability to 'switch' interaction partners (re-wiring). Qualitative data suggested a linear or slower than linear secondary extinction while quantitative data showed sigmoidal decline of plant interaction strength upon removal of the strongest interactor. Temporal snapshots indicated greater stability of re-wired networks over static systems. Tolerance of generalized networks to species extinctions was high in the random removal scenario, with an increase in network stability if species formed new interactions. Anthropogenic disturbance, however, that promote the extinction of the strongest interactors might induce a sudden collapse of pollination networks.

  15. Personalized Social Network Activity Feeds for Increased Interaction and Content Contribution

    Directory of Open Access Journals (Sweden)

    Shlomo eBerkovsky

    2015-10-01

    Full Text Available Online social networks were originally conceived as means of sharing information and activities with friends, and their success has been one of the primary contributors of the tremendous growth of the Web. Social network activity feeds were devised as a means to aggregate recent actions of friends into a convenient list. But the volume of actions and content generated by social network users is overwhelming, such that keeping users up-to-date with friend activities is an ongoing challenge for social network providers. Personalization has been proposed as a solution to combat social network information overload and help users to identify the nuggets of relevant information in the incoming flood of network activities. In this paper, we propose and thoroughly evaluate a personalized model for predicting the relevance of the activity feed items, which informs the ranking of the feeds and facilitates personalization. Results of a live study show that the proposed feed personalization approach successfully identifies and promotes relevant feed items and boosts the uptake of the feeds. In addition, it increases the contribution of user-generated content to the social network and spurs interaction between users.

  16. Effect of organic fertilizers on maize production in Eastern Georgia

    Science.gov (United States)

    Jolokhava, Tamar; Kenchiashvili, Naira; Tarkhnishvili, Maia; Ghambashidze, Giorgi

    2016-04-01

    Maize remains to be the most important cereal crop in Georgia. Total area of arable land under cereal crops production equals to 184 thousands hectares (FAO statistical yearbook, 2014), from which maize takes the biggest share. Leading position of maize among other cereal crops is caused by its dual purpose as food and feed product. In Spite of a relatively high production of maize to other cereals there is still a high demand on it, especially as feed for animal husbandry. The same tendency is seen in organic production, where producers of livestock and poultry products require organically grown maize, the average yield of which is much less than those produced conventionally. Therefore, it is important to increase productivity of maize in organic farms. Current study aimed to improve maize yield using locally produced organic fertilizers and to compare them to the effect of mineral fertilizers. The study was carried out in Eastern Georgia under dry subtropical climate conditions on local hybrid of maize. This is the first attempt to use hybrid maize (developed with organic plant breeding method) in organic field trials in Georgia. The results shown, that grain yield from two different types of organic fertilizers reached 70% of the yields achieved with industrial mineral fertilizers. As on farm level differences between organic and conventional maize production are much severe, the results from the field trials seems to be promising for future improvement of organic cereal crop production.

  17. Isolation and evolution of labile sulfur allotropes via kinetic encapsulation in interactive porous networks

    Directory of Open Access Journals (Sweden)

    Hakuba Kitagawa

    2016-07-01

    Full Text Available The isolation and characterization of small sulfur allotropes have long remained unachievable because of their extreme lability. This study reports the first direct observation of disulfur (S2 with X-ray crystallography. Sulfur gas was kinetically trapped and frozen into the pores of two Cu-based porous coordination networks containing interactive iodide sites. Stabilization of S2 was achieved either through physisorption or chemisorption on iodide anions. One of the networks displayed shape selectivity for linear molecules only, therefore S2 was trapped and remained stable within the material at room temperature and higher. In the second network, however, the S2 molecules reacted further to produce bent-S3 species as the temperature was increased. Following the thermal evolution of the S2 species in this network using X-ray diffraction and Raman spectroscopy unveiled the generation of a new reaction intermediate never observed before, the cyclo-trisulfur dication (cyclo-S32+. It is envisaged that kinetic guest trapping in interactive crystalline porous networks will be a promising method to investigate transient chemical species.

  18. The Effects of the Saakashvili Era Reforms on Informal Practices in the Republic of Georgia

    Directory of Open Access Journals (Sweden)

    Huseyn Aliyev

    2014-06-01

    Full Text Available Since the 2003 Rose Revolution, the Georgian government implemented a number of major institutional reforms which have succeeded in modernising Georgia’s state institutions, reducing corruption and ‘formalising’ the public sector. While the effects of Saakashvili’s reforms on state and institution-building, corruption and the rule of law have been examined by a large and growing body of academic literature, there has been little discussion about the impact of institutional changes on the previously widespread culture of informality in Georgia. This article explores the effects of Georgian institution-building from such aspects of informality as the use of informal networks and connections in exchanges of favours, gift-giving and other types of informal activities. The findings of this study, based on the analysis of recent surveys and in-depth interviews, conclude that the reforms succeeded in undermining the overall importance of informal practices in dealings with state bureaucracy, education system, healthcare, law enforcement, judiciary and some other areas previously dominated by informality. However, the reliance on informality did not disappear, and informal networks are still employed as coping mechanisms and as social safety nets.

  19. Women who inject drugs in the republic of georgia: in their own words.

    Science.gov (United States)

    Kirtadze, Irma; Otiashvili, David; O'Grady, Kevin; Zule, William; Krupitsky, Evgeny; Wechsberg, Wendee; Jones, Hendrée

    2015-01-01

    This study describes the initiation and maintenance of illicit drug use, risky behaviors, and the substance use treatment experiences of women in Georgia. Qualitative interviews with 55 drug-using women (mean age 36 years; SD = 9.52), were conducted during April-September 2011. Participants presented diverse histories of drug use initiation and substance use, risky behaviors, and drug treatment participation. All participants reported concurrent use of different substances, including home-produced injection preparations. Women described their experiences of both the positive and negative effects (physical and psychological) that they attributed to their use of drugs. Findings enrich our understanding of the environment in which substance use is initiated and maintained in a female population in Georgia, and illustrate the importance of culture and the role of social factors in the development of injection drug use. Results can provide direction for tailoring the development of interventions for substance use disorders, public policy discussions regarding the treatment of women who use drugs, and future research on substance use among women in Georgia and other post-Soviet nations.

  20. Interacting loop-current model of superconducting networks

    International Nuclear Information System (INIS)

    Chi, C.C.; Santhanam, P.; Bloechl, P.E.

    1992-01-01

    The authors review their recent approximation scheme to calculate the normal-superconducting phase boundary, T c (H), of a superconducting wire network in a magnetic field in terms of interacting loop currents. The theory is based on the London approximation of the linearized Ginzburg-Landau equation. An approximate general formula is derived for any two-dimensional space-filling lattice comprising tiles of two shapes. Many examples are provided illustrating the use of this method, with a particular emphasis on the fluxoid distribution. In addition to periodic lattices, quasiperiodic lattices and fractal Sierpinski gaskets are also discussed

  1. Network characteristics emerging from agent interactions in balanced distributed system.

    Science.gov (United States)

    Salman, Mahdi Abed; Bertelle, Cyrille; Sanlaville, Eric

    2015-01-01

    A distributed computing system behaves like a complex network, the interactions between nodes being essential information exchanges and migrations of jobs or services to execute. These actions are performed by software agents, which behave like the members of social networks, cooperating and competing to obtain knowledge and services. The load balancing consists in distributing the load evenly between system nodes. It aims at enhancing the resource usage. A load balancing strategy specifies scenarios for the cooperation. Its efficiency depends on quantity, accuracy, and distribution of available information. Nevertheless, the distribution of information on the nodes, together with the initial network structure, may create different logical network structures. In this paper, different load balancing strategies are tested on different network structures using a simulation. The four tested strategies are able to distribute evenly the load so that the system reaches a steady state (the mean response time of the jobs is constant), but it is shown that a given strategy indeed behaves differently according to structural parameters and information spreading. Such a study, devoted to distributed computing systems (DCSs), can be useful to understand and drive the behavior of other complex systems.

  2. Communicative language teaching in Georgia : from theory to practice

    NARCIS (Netherlands)

    Edisherashvili, Natalia

    2014-01-01

    In a globalizing world, the majority of language learners need to study foreign languages for real-life purposes, in order to be able to communicate beyond the bounds of their own country. This is especially important for the populations of smaller countries such as Georgia, whose native language is

  3. Carnegie Mellon's STUDIO for Creative Inquiry [and] The Interdisciplinary Teaching Network (ITeN) [and] Interactive Fiction [and] The Networked Virtual Art Museum.

    Science.gov (United States)

    Holden, Lynn; And Others

    1992-01-01

    Explains the STUDIO for Creative Inquiry, an interdisciplinary center at Carnegie Mellon University that supports experimental activities in the arts, and its Interdisciplinary Teaching Network. Three STUDIO projects are described: the Ancient Egypt Prototype application of the network; an interactive fiction system based on artificial…

  4. On Common Constitutional Ground: How Georgia's Scholarship Tax Credits Mirror Other State Programs and Expand Educational Opportunity

    Science.gov (United States)

    Carpenter, Dick M., II.; Erickson, Angela C.

    2016-01-01

    In 2008, Georgia launched a tax-credit scholarship program to expand educational opportunities for the state's pre-K through 12th-grade students by providing them scholarships to attend private schools. Georgia's scholarship tax credit program will help over 13,000 children get the best education for their needs at secular and religious private…

  5. Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

    Science.gov (United States)

    Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

    2015-11-01

    Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

  6. Positive Selection and Centrality in the Yeast and Fly Protein-Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Sandip Chakraborty

    2016-01-01

    Full Text Available Proteins within a molecular network are expected to be subject to different selective pressures depending on their relative hierarchical positions. However, it is not obvious what genes within a network should be more likely to evolve under positive selection. On one hand, only mutations at genes with a relatively high degree of control over adaptive phenotypes (such as those encoding highly connected proteins are expected to be “seen” by natural selection. On the other hand, a high degree of pleiotropy at these genes is expected to hinder adaptation. Previous analyses of the human protein-protein interaction network have shown that genes under long-term, recurrent positive selection (as inferred from interspecific comparisons tend to act at the periphery of the network. It is unknown, however, whether these trends apply to other organisms. Here, we show that long-term positive selection has preferentially targeted the periphery of the yeast interactome. Conversely, in flies, genes under positive selection encode significantly more connected and central proteins. These observations are not due to covariation of genes’ adaptability and centrality with confounding factors. Therefore, the distribution of proteins encoded by genes under recurrent positive selection across protein-protein interaction networks varies from one species to another.

  7. Georgia Economic Report, October 2013 : Seeking Effective Policies

    OpenAIRE

    World Bank

    2013-01-01

    This economic report records the economic activities of Georgia for the year 2013. The growth slow-down in 2013, largely viewed as temporary, reflected to a large extent policy uncertainty that began with the late-2012 parliamentary elections and is expected to last until the October 2013 Presidential elections, and attempts by the new government to trim public investment spending. In the ...

  8. Biotechnology in Georgia for Various Applications

    International Nuclear Information System (INIS)

    Mosulishvili, L.; Tsibakhashvili, N.; Kirkesali, E.; Tsertsvadze, L.; Frontasyeva, M.; Pavlov, S.

    2008-01-01

    The results of collaborative work carried out in the field of biotechnology at the Frank Laboratory of Neutron Physics (FLNP) of the Joint Institute for Nuclear Research (JINR) (Dubna, Russia) jointly with scientists from Georgia are presented. Using instrumental neutron activation analysis (NAA), significant results were ontained in the following directions - medical biotechnology, environmental biotechnology and industrial biotechnology. In the biomedical experiments a blue-green alga Spirulina platensis biomass has been used as a matrix for the development of pharmaceutical substances containing such vitally important trace elements as selenium, chromium and iodine. The feasibility of target-oriented introduction of these elements into Spirulina platensis biocomplexes retaining its protain composition and natural beneficial properties has been proved. The adsorption of such toxic metal as mercury by Spirulina platensis biomass in dynamics of growth has been studied also. NAA has been successfully applied to investigate the biotechnology of toxic Cr(VI) transformation into less toxic Cr(III) complexes by Cr(VI)-reducer bacteria isolated from polluted basalts in Georgia. This method was used to track accumulation of chromium in the bacterial cells. To monitor and identify Cr(III) complexes in these bacteria, electron spin resonance (ESR) spectrometry was employed. For the first time, the elemental composition of Cr(VI)-reducer bacteria has been studied using epithermal NAA. The natural organic mass of vegetal origin - peat - was applied as a source of microorganisms to study the bacterial leaching of some metals from lean ores, rocks and industrial wastes. (author)

  9. Comprehension through explanation as the interaction of the brain’s coherence and cognitive control networks

    Directory of Open Access Journals (Sweden)

    Jarrod eMoss

    2015-10-01

    Full Text Available Discourse comprehension processes attempt to produce an elaborate and well-connected representation in the reader’s mind. A common network of regions including the angular gyrus, posterior cingulate, and dorsal frontal cortex appears to be involved in constructing coherent representations in a variety of tasks including social cognition tasks, narrative comprehension, and expository text comprehension. Reading strategies that require the construction of explicit inferences are used in the present research to examine how this coherence network interacts with other brain regions. A psychophysiological interaction analysis was used to examine regions showing changed functional connectivity with this coherence network when participants were engaged in either a non-inferencing reading strategy, paraphrasing, or a strategy requiring coherence-building inferences, self-explanation. Results of the analysis show that the coherence network increases in functional connectivity with a cognitive control network that may be specialized for the manipulation of semantic representations and the construction of new relations among these representations.

  10. Multilayer networks reveal the spatial structure of seed-dispersal interactions across the Great Rift landscapes.

    Science.gov (United States)

    Timóteo, Sérgio; Correia, Marta; Rodríguez-Echeverría, Susana; Freitas, Helena; Heleno, Ruben

    2018-01-10

    Species interaction networks are traditionally explored as discrete entities with well-defined spatial borders, an oversimplification likely impairing their applicability. Using a multilayer network approach, explicitly accounting for inter-habitat connectivity, we investigate the spatial structure of seed-dispersal networks across the Gorongosa National Park, Mozambique. We show that the overall seed-dispersal network is composed by spatially explicit communities of dispersers spanning across habitats, functionally linking the landscape mosaic. Inter-habitat connectivity determines spatial structure, which cannot be accurately described with standard monolayer approaches either splitting or merging habitats. Multilayer modularity cannot be predicted by null models randomizing either interactions within each habitat or those linking habitats; however, as habitat connectivity increases, random processes become more important for overall structure. The importance of dispersers for the overall network structure is captured by multilayer versatility but not by standard metrics. Highly versatile species disperse many plant species across multiple habitats, being critical to landscape functional cohesion.

  11. Drivers and Effects of Groundwater-Surface Water Interaction in the Karstic Lower Flint River Basin, Southwestern Georgia, USA

    Science.gov (United States)

    Rugel, K.; Golladay, S. W.; Jackson, C. R.; Rasmussen, T. C.; Dowd, J. F.; Mcdowell, R. J.

    2017-12-01

    Groundwater provides the majority of global water resources for domestic and agricultural usage while contributing vital surface water baseflows which support healthy aquatic ecosystems. Understanding the extent and magnitude of hydrologic connectivity between groundwater and surface water components in karst watersheds is essential to the prudent management of these hydraulically-interactive systems. We examined groundwater and surface water connectivity between the Upper Floridan Aquifer (UFA) and streams in the Lower Flint River Basin (LFRB) in southwestern Georgia where development of agricultural irrigation intensified over the past 30 years. An analysis of USGS streamflow data for the pre- and post-irrigation period showed summer baseflows in some Lower Flint River tributaries were reduced by an order of magnitude in the post-irrigation period, reiterating the strong hydraulic connection between these streams and the underlying aquifer. Large and fine-scale monitoring of calcium, nitrate, specific conductance and stable isotopes (δ18O and δD) on 50 km of Ichawaynochaway Creek, a major tributary of the Lower Flint, detected discrete groundwater-surface water flow paths which accounted for 42% of total groundwater contributions in the 50 km study reach. This presentation will highlight a new analysis using the metadata EPA Reach File (1) and comparing stream reach and instream bedrock joint azimuths with stream geochemical results from previous field study. Our findings suggested that reaches with NNW bearing may be more likely to display enhanced groundwater-surface water connectivity. Our results show that local heterogeneity can significantly affect water budgets and quality within these watersheds, making the use of geomorphological stream attributes a valuable tool to water resource management for the prediction and protection of vulnerable regions of hydrologic connectivity in karst catchments.

  12. Design and performance of the Georgia Tech Aquatic Center photovoltaic system. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Rohatgi, A.; Begovic, M.; Long, R.; Ropp, M.; Pregelj, A.

    1996-12-31

    A building-integrated DC PV array has been constructed on the Georgia Tech campus. The array is mounted on the roof of the Georgia Tech Aquatic Center (GTAC), site of the aquatic events during the 1996 Paralympic and Olympic Games in Atlanta. At the time of its construction, it was the world`s largest roof-mounted photovoltaic array, comprised of 2,856 modules and rates at 342 kW. This section describes the electrical and physical layout of the PV system, and the associated data acquisition system (DAS) which monitors the performance of the system and collects measurements of several important meteorological parameters.

  13. The role of asymmetric interactions on the effect of habitat destruction in mutualistic networks.

    Directory of Open Access Journals (Sweden)

    Guillermo Abramson

    Full Text Available Plant-pollinator mutualistic networks are asymmetric in their interactions: specialist plants are pollinated by generalist animals, while generalist plants are pollinated by a broad range involving specialists and generalists. It has been suggested that this asymmetric--or disassortative--assemblage could play an important role in determining the observed equal susceptibility of specialist and generalist plants under habitat destruction. At the core of the analysis of the phenomenon lies the observation that specialist plants, otherwise candidates to extinction, could cope with the disruption thanks to their interaction with a few generalist pollinators. We present a theoretical framework that supports this thesis. We analyze a dynamical model of a system of mutualistic plants and pollinators, subject to the destruction of their habitat. We analyze and compare two families of interaction topologies, ranging from highly assortative to highly disassortative ones, as well as real pollination networks. We found that several features observed in natural systems are predicted by the mathematical model. First, there is a tendency to increase the asymmetry of the network as a result of the extinctions. Second, an entropy measure of the differential susceptibility to extinction of specialist and generalist species show that they tend to balance when the network is disassortative. Finally, the disappearance of links in the network, as a result of extinctions, shows that specialist plants preserve more connections than the corresponding plants in an assortative system, enabling them to resist the disruption.

  14. Artificial neural network inference (ANNI: a study on gene-gene interaction for biomarkers in childhood sarcomas.

    Directory of Open Access Journals (Sweden)

    Dong Ling Tong

    Full Text Available OBJECTIVE: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI. METHOD: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model. RESULTS: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS; FCGRT and OLFM1 in Ewing's sarcoma (EWS suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen. CONCLUSIONS: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas.

  15. Digital Learning Compass: Distance Education State Almanac 2017. Georgia

    Science.gov (United States)

    Seaman, Julia E.; Seaman, Jeff

    2017-01-01

    This brief report uses data collected under the U.S. Department of Education's National Center for Educational Statistics (NCES) Integrated Postsecondary Education Data System (IPEDS) Fall Enrollment survey to highlight distance education data in the state of Georgia. The sample for this analysis is comprised of all active, degree-granting…

  16. ANSIBLE: A Network of Social Interactions for Bilateral Life Enhancement, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — ANSIBLE (A Network of Social Interactions for Bilateral Life Enhancement) can be used pre, during, and post flight to connect the flight crew with their family,...

  17. HKC: An Algorithm to Predict Protein Complexes in Protein-Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Xiaomin Wang

    2011-01-01

    Full Text Available With the availability of more and more genome-scale protein-protein interaction (PPI networks, research interests gradually shift to Systematic Analysis on these large data sets. A key topic is to predict protein complexes in PPI networks by identifying clusters that are densely connected within themselves but sparsely connected with the rest of the network. In this paper, we present a new topology-based algorithm, HKC, to detect protein complexes in genome-scale PPI networks. HKC mainly uses the concepts of highest k-core and cohesion to predict protein complexes by identifying overlapping clusters. The experiments on two data sets and two benchmarks show that our algorithm has relatively high F-measure and exhibits better performance compared with some other methods.

  18. Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

    Directory of Open Access Journals (Sweden)

    Recep Colak

    2010-10-01

    Full Text Available Computational prediction of functionally related groups of genes (functional modules from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented.We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB, by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples.We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely

  19. Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

    Science.gov (United States)

    Colak, Recep; Moser, Flavia; Chu, Jeffrey Shih-Chieh; Schönhuth, Alexander; Chen, Nansheng; Ester, Martin

    2010-10-25

    Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense) regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB), by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely available large

  20. Integrating probabilistic models of perception and interactive neural networks: a historical and tutorial review.

    Science.gov (United States)

    McClelland, James L

    2013-01-01

    This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interactive activation (IA) model of perception. The article is in part an historical review and in part a tutorial, reviewing the probabilistic Bayesian approach to understanding perception and how it may be shaped by context, and also reviewing ideas about how such probabilistic computations may be carried out in neural networks, focusing on the role of context in interactive neural networks, in which both bottom-up and top-down signals affect the interpretation of sensory inputs. It is pointed out that connectionist units that use the logistic or softmax activation functions can exactly compute Bayesian posterior probabilities when the bias terms and connection weights affecting such units are set to the logarithms of appropriate probabilistic quantities. Bayesian concepts such the prior, likelihood, (joint and marginal) posterior, probability matching and maximizing, and calculating vs. sampling from the posterior are all reviewed and linked to neural network computations. Probabilistic and neural network models are explicitly linked to the concept of a probabilistic generative model that describes the relationship between the underlying target of perception (e.g., the word intended by a speaker or other source of sensory stimuli) and the sensory input that reaches the perceiver for use in inferring the underlying target. It is shown how a new version of the IA model called the multinomial interactive activation (MIA) model can sample correctly from the joint posterior of a proposed generative model for perception of letters in words, indicating that interactive processing is fully consistent with principled probabilistic computation. Ways in which these computations might be realized in real neural systems are also considered.

  1. Computer Networks E-learning Based on Interactive Simulations and SCORM

    Directory of Open Access Journals (Sweden)

    Francisco Andrés Candelas

    2011-05-01

    Full Text Available This paper introduces a new set of compact interactive simulations developed for the constructive learning of computer networks concepts. These simulations, which compose a virtual laboratory implemented as portable Java applets, have been created by combining EJS (Easy Java Simulations with the KivaNS API. Furthermore, in this work, the skills and motivation level acquired by the students are evaluated and measured when these simulations are combined with Moodle and SCORM (Sharable Content Object Reference Model documents. This study has been developed to improve and stimulate the autonomous constructive learning in addition to provide timetable flexibility for a Computer Networks subject.

  2. Minimum curvilinearity to enhance topological prediction of protein interactions by network embedding

    KAUST Repository

    Cannistraci, Carlo; Alanis Lobato, Gregorio; Ravasi, Timothy

    2013-01-01

    Motivation: Most functions within the cell emerge thanks to protein-protein interactions (PPIs), yet experimental determination of PPIs is both expensive and time-consuming. PPI networks present significant levels of noise and incompleteness

  3. A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations

    Directory of Open Access Journals (Sweden)

    Jan eHahne

    2015-09-01

    Full Text Available Contemporary simulators for networks of point and few-compartment model neurons come with a plethora of ready-to-use neuron and synapse models and support complex network topologies. Recent technological advancements have broadened the spectrum of application further to the efficient simulation of brain-scale networks on supercomputers. In distributed network simulations the amount of spike data that accrues per millisecond and process is typically low, such that a common optimization strategy is to communicate spikes at relatively long intervals, where the upper limit is given by the shortest synaptic transmission delay in the network. This approach is well-suited for simulations that employ only chemical synapses but it has so far impeded the incorporation of gap-junction models, which require instantaneous neuronal interactions. Here, we present a numerical algorithm based on a waveform-relaxation technique which allows for network simulations with gap junctions in a way that is compatible with the delayed communication strategy. Using a reference implementation in the NEST simulator, we demonstrate that the algorithm and the required data structures can be smoothly integrated with existing code such that they complement the infrastructure for spiking connections. To show that the unified framework for gap-junction and spiking interactions achieves high performance and delivers high accuracy...

  4. NITROUS OXIDE CONCENTRATIONS IN SMALL STREAMS OF THE GEORGIA PIEDMONT

    Science.gov (United States)

    We are measuring the dissolved nitrous oxide concentration in 17 headwater streams in the South Fork Broad River, Georgia watershed on a monthly basis. The selected small streams drain watersheds dominated by forest, pasture, developed, or mixed land uses. Nitrous oxide concentr...

  5. Biana: a software framework for compiling biological interactions and analyzing networks.

    Science.gov (United States)

    Garcia-Garcia, Javier; Guney, Emre; Aragues, Ramon; Planas-Iglesias, Joan; Oliva, Baldo

    2010-01-27

    The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties. We introduce BIANA (Biologic Interactions and Network Analysis), a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i) the integration of multiple sources of biological information, including biological entities and their relationships, and ii) the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php. BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules.

  6. CAUSALITY RELATIONSHIP BETWEEN GDP AND ENERGY CONSUMPTION IN GEORGIA, AZERBAIJAN AND ARMENIA

    Directory of Open Access Journals (Sweden)

    Huseyin Kalyoncu

    2013-01-01

    Full Text Available This research aims to investigate the relationship between energy consumption and economic growth in Georgia, Azerbaijan and Armenia during the period of 1995–2009. The Engle-Granger cointegration and Granger causality tests are used in order to analyse the causal relationship between energy consumption and economic growth. It is crucial to see the directions of causality between two variables for the policy makers. For Georgia and Azerbaijan it is found that these two variables are not cointegrated. In case of Armenia these two variables are cointegrated. Accordingly, causality analysis is conducted for Armenia. The research outcomes reveal that there is unidirectional causality from per capita GDP to per capita energy consumption for Armenia.

  7. Urgent Problems in Learning the Public Administration (on the Example of Georgia

    Directory of Open Access Journals (Sweden)

    Shota Dogonadze

    2011-12-01

    Full Text Available Public management can and should be taught. Former Soviet Republics, including Georgia are facing this acute problem. Some attention is directed to management training, but public management stays in the background, although it is evident that major political and economic problems of Georgia and other countries of so-called “fledging democracies” arise due to the government theory neglect. The article considers development of administrative way of thinking starting from political doctrine to managerial approach, prospects for public management principles development, existing educational models. The epoch of classic universities is passing; with the help of textbooks students can only make courseworks. That’s why the use of innovative methods is necessary for students training.

  8. Modeling attacker-defender interactions in information networks.

    Energy Technology Data Exchange (ETDEWEB)

    Collins, Michael Joseph

    2010-09-01

    The simplest conceptual model of cybersecurity implicitly views attackers and defenders as acting in isolation from one another: an attacker seeks to penetrate or disrupt a system that has been protected to a given level, while a defender attempts to thwart particular attacks. Such a model also views all non-malicious parties as having the same goal of preventing all attacks. But in fact, attackers and defenders are interacting parts of the same system, and different defenders have their own individual interests: defenders may be willing to accept some risk of successful attack if the cost of defense is too high. We have used game theory to develop models of how non-cooperative but non-malicious players in a network interact when there is a substantial cost associated with effective defensive measures. Although game theory has been applied in this area before, we have introduced some novel aspects of player behavior in our work, including: (1) A model of how players attempt to avoid the costs of defense and force others to assume these costs; (2) A model of how players interact when the cost of defending one node can be shared by other nodes; and (3) A model of the incentives for a defender to choose less expensive, but less effective, defensive actions.

  9. Evaluation of clustering algorithms for protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    van Helden Jacques

    2006-11-01

    Full Text Available Abstract Background Protein interactions are crucial components of all cellular processes. Recently, high-throughput methods have been developed to obtain a global description of the interactome (the whole network of protein interactions for a given organism. In 2002, the yeast interactome was estimated to contain up to 80,000 potential interactions. This estimate is based on the integration of data sets obtained by various methods (mass spectrometry, two-hybrid methods, genetic studies. High-throughput methods are known, however, to yield a non-negligible rate of false positives, and to miss a fraction of existing interactions. The interactome can be represented as a graph where nodes correspond with proteins and edges with pairwise interactions. In recent years clustering methods have been developed and applied in order to extract relevant modules from such graphs. These algorithms require the specification of parameters that may drastically affect the results. In this paper we present a comparative assessment of four algorithms: Markov Clustering (MCL, Restricted Neighborhood Search Clustering (RNSC, Super Paramagnetic Clustering (SPC, and Molecular Complex Detection (MCODE. Results A test graph was built on the basis of 220 complexes annotated in the MIPS database. To evaluate the robustness to false positives and false negatives, we derived 41 altered graphs by randomly removing edges from or adding edges to the test graph in various proportions. Each clustering algorithm was applied to these graphs with various parameter settings, and the clusters were compared with the annotated complexes. We analyzed the sensitivity of the algorithms to the parameters and determined their optimal parameter values. We also evaluated their robustness to alterations of the test graph. We then applied the four algorithms to six graphs obtained from high-throughput experiments and compared the resulting clusters with the annotated complexes. Conclusion This

  10. The Social Fabric of Elementary Schools: A Network Typology of Social Interaction among Teachers

    Science.gov (United States)

    Moolenaar, Nienke M.; Sleegers, Peter J. C.; Karsten, Sjoerd; Daly, Alan J.

    2012-01-01

    While researchers are currently studying various forms of social network interaction among teachers for their impact on educational policy implementation and practice, knowledge on how various types of networks are interrelated is limited. The goal of this study is to understand the dimensionality that may underlie various types of social networks…

  11. In-silico studies of neutral drift for functional protein interaction networks

    Science.gov (United States)

    Ali, Md Zulfikar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

    We have developed a minimal physically-motivated model of protein-protein interaction networks. Our system consists of two classes of enzymes, activators (e.g. kinases) and deactivators (e.g. phosphatases), and the enzyme-mediated activation/deactivation rates are determined by sequence-dependent binding strengths between enzymes and their targets. The network is evolved by introducing random point mutations in the binding sequences where we assume that each new mutation is either fixed or entirely lost. We apply this model to studies of neutral drift in networks that yield oscillatory dynamics, where we start, for example, with a relatively simple network and allow it to evolve by adding nodes and connections while requiring that dynamics be conserved. Our studies demonstrate both the importance of employing a sequence-based evolutionary scheme and the relative rapidity (in evolutionary time) for the redistribution of function over new nodes via neutral drift. Surprisingly, in addition to this redistribution time we discovered another much slower timescale for network evolution, reflecting hidden order in sequence space that we interpret in terms of sparsely connected domains.

  12. Simulated tri-trophic networks reveal complex relationships between species diversity and interaction diversity.

    Science.gov (United States)

    Pardikes, Nicholas A; Lumpkin, Will; Hurtado, Paul J; Dyer, Lee A

    2018-01-01

    Most of earth's biodiversity is comprised of interactions among species, yet it is unclear what causes variation in interaction diversity across space and time. We define interaction diversity as the richness and relative abundance of interactions linking species together at scales from localized, measurable webs to entire ecosystems. Large-scale patterns suggest that two basic components of interaction diversity differ substantially and predictably between different ecosystems: overall taxonomic diversity and host specificity of consumers. Understanding how these factors influence interaction diversity, and quantifying the causes and effects of variation in interaction diversity are important goals for community ecology. While previous studies have examined the effects of sampling bias and consumer specialization on determining patterns of ecological networks, these studies were restricted to two trophic levels and did not incorporate realistic variation in species diversity and consumer diet breadth. Here, we developed a food web model to generate tri-trophic ecological networks, and evaluated specific hypotheses about how the diversity of trophic interactions and species diversity are related under different scenarios of species richness, taxonomic abundance, and consumer diet breadth. We investigated the accumulation of species and interactions and found that interactions accumulate more quickly; thus, the accumulation of novel interactions may require less sampling effort than sampling species in order to get reliable estimates of either type of diversity. Mean consumer diet breadth influenced the correlation between species and interaction diversity significantly more than variation in both species richness and taxonomic abundance. However, this effect of diet breadth on interaction diversity is conditional on the number of observed interactions included in the models. The results presented here will help develop realistic predictions of the relationships

  13. Are Lesbian, Gay, Bisexual and Transgender (LGBT) persons protected against discrimination and hate crime in Georgia?

    OpenAIRE

    Japaridze, Sophio

    2012-01-01

    This article discusses whether lesbian, gay, bisexual and transgender (LGBT) people are protected against discrimination and hate crime in Georgia. Georgia is dominated by deeply rooted traditions, history and religion which promote stigmatisation and enhance existing negative stereotypes of the LGBT community. This is aggravated by state practice and poor legislation which fail to ensure adequate protection of LGBT individuals against discrimination and hate crime. Even though homosexuality ...

  14. Music Circulation and Transmission in Tbilisi, Georgia

    OpenAIRE

    Sebald, Brigita

    2013-01-01

    This dissertation, based upon two years research in Tbilisi, Georgia, questions how popular music travels from the performer to the audience and how it circulates among audience members. After the disintegration of the Soviet Union in the early 1990s, the state-run music industry collapsed, taking the infrastructure for music distribution with it. In the years since, a music industry has not been rebuilt due to uncertain economic realities and a shaky political situation. Because of this, per...

  15. 2016 Morgan County, Georgia ADS100 4-Band 8 Bit Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of 0.5-foot pixel resolution, natural color orthoimages covering Morgan County, Georgia. An orthoimage is remotely sensed image data in which...

  16. 2016 Walton County, Georgia ADS100 4-Band 8 Bit Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of 0.5-foot pixel resolution, natural color orthoimages covering Walton County, Georgia. An orthoimage is remotely sensed image data in which...

  17. 2016 Oconee County, Georgia ADS100 4-Band 8 Bit Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of 0.5-foot pixel resolution, natural color orthoimages covering Oconee County, Georgia. An orthoimage is remotely sensed image data in which...

  18. 2016 Newton County, Georgia ADS100 4-Band 8 Bit Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of 0.5-foot pixel resolution, natural color orthoimages covering Newton County, Georgia. An orthoimage is remotely sensed image data in which...

  19. Investigating student communities with network analysis of interactions in a physics learning center

    Directory of Open Access Journals (Sweden)

    Eric Brewe

    2012-01-01

    Full Text Available Developing a sense of community among students is one of the three pillars of an overall reform effort to increase participation in physics, and the sciences more broadly, at Florida International University. The emergence of a research and learning community, embedded within a course reform effort, has contributed to increased recruitment and retention of physics majors. We utilize social network analysis to quantify interactions in Florida International University’s Physics Learning Center (PLC that support the development of academic and social integration. The tools of social network analysis allow us to visualize and quantify student interactions and characterize the roles of students within a social network. After providing a brief introduction to social network analysis, we use sequential multiple regression modeling to evaluate factors that contribute to participation in the learning community. Results of the sequential multiple regression indicate that the PLC learning community is an equitable environment as we find that gender and ethnicity are not significant predictors of participation in the PLC. We find that providing students space for collaboration provides a vital element in the formation of a supportive learning community.

  20. Investigating student communities with network analysis of interactions in a physics learning center

    Science.gov (United States)

    Brewe, Eric; Kramer, Laird; Sawtelle, Vashti

    2012-06-01

    Developing a sense of community among students is one of the three pillars of an overall reform effort to increase participation in physics, and the sciences more broadly, at Florida International University. The emergence of a research and learning community, embedded within a course reform effort, has contributed to increased recruitment and retention of physics majors. We utilize social network analysis to quantify interactions in Florida International University’s Physics Learning Center (PLC) that support the development of academic and social integration. The tools of social network analysis allow us to visualize and quantify student interactions and characterize the roles of students within a social network. After providing a brief introduction to social network analysis, we use sequential multiple regression modeling to evaluate factors that contribute to participation in the learning community. Results of the sequential multiple regression indicate that the PLC learning community is an equitable environment as we find that gender and ethnicity are not significant predictors of participation in the PLC. We find that providing students space for collaboration provides a vital element in the formation of a supportive learning community.

  1. Reality of Risk of Natural Disasters in Georgia and a Management Policy

    Science.gov (United States)

    Gaprindashvili, George; Tsereteli, Emil; Gobejishvili, Ramin; King, Lorenz; Gaprindashvili, Merab

    2013-04-01

    In the last decades of the 20th century, the protection of the population from natural disasters, the preservation of land resources and the safe operation of a complex infrastructure and costly engineering facilities have become the primary socio-economic, demographic, political and environmental problems worldwide. This problem has become more acute in recent years when the natural cataclysms in terms of a population increase, progressive urbanization and use of vulnerable technologies have acquired even larger scales. This holds true especially for mountainous countries as Georgia, too. Natural-catastrophic processes as landslides, mudflows, rockfalls and erosion, and their frequent reoccurrence with harmful impacts to population, agricultural lands and engineering objects form a demanding challenge for the responsible authorities. Thousands of settlements, roads, oil and gas pipelines, high-voltage power transmission lines and other infrastructure may be severely damaged. Respective studies prove that the origin and activation of landslide-gravitational and mudflow processes increase year by year, and this holds true for almost all landscapes and geomorphological zones of Georgia. Catastrophic events may be triggered by (1) intense earthquakes, (2) extreme hydro-meteorological events, probably on the background of global climatic changes (3) large-scale human impacts on the environment. Societies with a low level of preparedness concerning these hazards are especially hit hard. In view of this urgent task, many departmental and research institutions have increased their efforts within the limits of their competence. First of all, it is the activity of the Geological Survey of Georgia (at present included in the National Environmental Agency of the Ministry of Environment Protection of Georgia) which mapped, identified and catalogued the hazardous processes on the territory of the country and identified the spatial limits and occurrences of hazardous processes

  2. Supply Chain Management: from Linear Interactions to Networked Processes

    Directory of Open Access Journals (Sweden)

    Doina FOTACHE

    2006-01-01

    Full Text Available Supply Chain Management is a distinctive product, with a tremendous impact on the software applications market. SCM applications are back-end solutions intended to link suppliers, manufacturers, distributors and resellers in a production and distribution network, which allows the enterprise to track and consolidate the flows of materials and data trough the process of manufacturing and distribution of goods/services. The advent of the Web as a major means of conducting business transactions and business-tobusiness communications, coupled with evolving web-based supply chain management (SCM technology, has resulted in a transition period from “linear” supply chain models to "networked" supply chain models. The technologies to enable dynamic process changes and real time interactions between extended supply chain partners are emerging and being deployed at an accelerated pace.

  3. Graph theoretic analysis of protein interaction networks of eukaryotes

    Science.gov (United States)

    Goh, K.-I.; Kahng, B.; Kim, D.

    2005-11-01

    Owing to the recent progress in high-throughput experimental techniques, the datasets of large-scale protein interactions of prototypical multicellular species, the nematode worm Caenorhabditis elegans and the fruit fly Drosophila melanogaster, have been assayed. The datasets are obtained mainly by using the yeast hybrid method, which contains false-positive and false-negative simultaneously. Accordingly, while it is desirable to test such datasets through further wet experiments, here we invoke recent developed network theory to test such high-throughput datasets in a simple way. Based on the fact that the key biological processes indispensable to maintaining life are conserved across eukaryotic species, and the comparison of structural properties of the protein interaction networks (PINs) of the two species with those of the yeast PIN, we find that while the worm and yeast PIN datasets exhibit similar structural properties, the current fly dataset, though most comprehensively screened ever, does not reflect generic structural properties correctly as it is. The modularity is suppressed and the connectivity correlation is lacking. Addition of interologs to the current fly dataset increases the modularity and enhances the occurrence of triangular motifs as well. The connectivity correlation function of the fly, however, remains distinct under such interolog additions, for which we present a possible scenario through an in silico modeling.

  4. 75 FR 67950 - The University of Georgia (UGA), et al.;

    Science.gov (United States)

    2010-11-04

    ... DEPARTMENT OF COMMERCE International Trade Administration The University of Georgia (UGA), et al.; Notice of Decision on Applications for Duty-Free Entry of Scientific Instruments This is a decision pursuant to Section 6(c) of the Educational, Scientific, and Cultural Materials Importation Act of 1966...

  5. The missing part of seed dispersal networks: structure and robustness of bat-fruit interactions.

    Directory of Open Access Journals (Sweden)

    Marco Aurelio Ribeiro Mello

    2011-02-01

    Full Text Available Mutualistic networks are crucial to the maintenance of ecosystem services. Unfortunately, what we know about seed dispersal networks is based only on bird-fruit interactions. Therefore, we aimed at filling part of this gap by investigating bat-fruit networks. It is known from population studies that: (i some bat species depend more on fruits than others, and (ii that some specialized frugivorous bats prefer particular plant genera. We tested whether those preferences affected the structure and robustness of the whole network and the functional roles of species. Nine bat-fruit datasets from the literature were analyzed and all networks showed lower complementary specialization (H(2' = 0.37±0.10, mean ± SD and similar nestedness (NODF = 0.56±0.12 than pollination networks. All networks were modular (M = 0.32±0.07, and had on average four cohesive subgroups (modules of tightly connected bats and plants. The composition of those modules followed the genus-genus associations observed at population level (Artibeus-Ficus, Carollia-Piper, and Sturnira-Solanum, although a few of those plant genera were dispersed also by other bats. Bat-fruit networks showed high robustness to simulated cumulative removals of both bats (R = 0.55±0.10 and plants (R = 0.68±0.09. Primary frugivores interacted with a larger proportion of the plants available and also occupied more central positions; furthermore, their extinction caused larger changes in network structure. We conclude that bat-fruit networks are highly cohesive and robust mutualistic systems, in which redundancy is high within modules, although modules are complementary to each other. Dietary specialization seems to be an important structuring factor that affects the topology, the guild structure and functional roles in bat-fruit networks.

  6. Georgia Health – Go Local: Using Multidisciplinary Partnerships to Promote a Statewide Consumer Health Website

    OpenAIRE

    Smith, Rita B.

    2011-01-01

    The National Library of Medicine ended its support of the Go Local program in 2010 due to declining usage, but in many ways Georgia's project was a success. From its beginning, Georgia Health – Go Local was a model of successful collaboration among a variety of partners and institutions throughout the state. The high usage statistics for the Go Local website and the support garnered by the project exemplify the positive nature of the collaborations that made the project possible.

  7. A protein interaction atlas for the nuclear receptors: properties and quality of a hub-based dimerisation network

    Directory of Open Access Journals (Sweden)

    De Graaf David

    2007-07-01

    Full Text Available Abstract Background The nuclear receptors are a large family of eukaryotic transcription factors that constitute major pharmacological targets. They exert their combinatorial control through homotypic heterodimerisation. Elucidation of this dimerisation network is vital in order to understand the complex dynamics and potential cross-talk involved. Results Phylogeny, protein-protein interactions, protein-DNA interactions and gene expression data have been integrated to provide a comprehensive and up-to-date description of the topology and properties of the nuclear receptor interaction network in humans. We discriminate between DNA-binding and non-DNA-binding dimers, and provide a comprehensive interaction map, that identifies potential cross-talk between the various pathways of nuclear receptors. Conclusion We infer that the topology of this network is hub-based, and much more connected than previously thought. The hub-based topology of the network and the wide tissue expression pattern of NRs create a highly competitive environment for the common heterodimerising partners. Furthermore, a significant number of negative feedback loops is present, with the hub protein SHP [NR0B2] playing a major role. We also compare the evolution, topology and properties of the nuclear receptor network with the hub-based dimerisation network of the bHLH transcription factors in order to identify both unique themes and ubiquitous properties in gene regulation. In terms of methodology, we conclude that such a comprehensive picture can only be assembled by semi-automated text-mining, manual curation and integration of data from various sources.

  8. Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs

    LENUS (Irish Health Repository)

    Casey, Fergal

    2011-08-22

    Abstract Background Gene and protein interactions are commonly represented as networks, with the genes or proteins comprising the nodes and the relationship between them as edges. Motifs, or small local configurations of edges and nodes that arise repeatedly, can be used to simplify the interpretation of networks. Results We examined triplet motifs in a network of quantitative epistatic genetic relationships, and found a non-random distribution of particular motif classes. Individual motif classes were found to be associated with different functional properties, suggestive of an underlying biological significance. These associations were apparent not only for motif classes, but for individual positions within the motifs. As expected, NNN (all negative) motifs were strongly associated with previously reported genetic (i.e. synthetic lethal) interactions, while PPP (all positive) motifs were associated with protein complexes. The two other motif classes (NNP: a positive interaction spanned by two negative interactions, and NPP: a negative spanned by two positives) showed very distinct functional associations, with physical interactions dominating for the former but alternative enrichments, typical of biochemical pathways, dominating for the latter. Conclusion We present a model showing how NNP motifs can be used to recognize supportive relationships between protein complexes, while NPP motifs often identify opposing or regulatory behaviour between a gene and an associated pathway. The ability to use motifs to point toward underlying biological organizational themes is likely to be increasingly important as more extensive epistasis mapping projects in higher organisms begin.

  9. Depth of interaction detection with enhanced position-sensitive proportional resistor network

    International Nuclear Information System (INIS)

    Lerche, Ch.W.; Benlloch, J.M.; Sanchez, F.; Pavon, N.; Gimenez, N.; Fernandez, M.; Gimenez, M.; Sebastia, A.; Martinez, J.; Mora, F.J.

    2005-01-01

    A new method of determining the depth of interaction of γ-rays in thick inorganic scintillation crystals was tested experimentally. The method uses the strong correlation between the width of the scintillation light distribution within large continuous crystals and the γ-ray's interaction depth. This behavior was successfully reproduced by a theoretical model distribution based on the inverse square law. For the determination of the distribution's width, its standard deviation σ is computed using an enhanced position-sensitive proportional resistor network which is often used in γ-ray-imaging devices. Minor changes of this known resistor network allow the analog and real-time determination of the light distribution's 2nd moment without impairing the measurement of the energy and centroid. First experimental results are presented that confirm that the described method works correctly. Since only some cheap electronic components, but no additional detectors or crystals are required, the main advantage of this method is its low cost

  10. Georgia fishery study: implications for dose calculations

    International Nuclear Information System (INIS)

    Turcotte, M.D.S.

    1983-01-01

    Fish consumption will contribute a major portion of the estimated individual and population doses from L-Reactor liquid releases and Cs-137 remobilization in Steel Creek. It is therefore important that the values for fish consumption used in dose calculations be as realistic as possible. Since publication of the L-Reactor Environmental Information Document (EID), data have become available on sport fishing in the Savannah River. These data provide SRP with site-specific sport fish harvest and consumption values for use in dose calculations. The Georgia fishery data support the total population fish consumption and calculated dose reported in the EID. The data indicate, however, that both the EID average and maximum individual fish consumption have been underestimated, although each to a different degree. The average fish consumption value used in the EID is approximately 3% below the lower limit of the fish consumption range calculated using the Georgia data. A fish consumption value of 11.3 kg/yr should be used to recalculate dose to the average individual from L-Reactor restart. Maximum fish consumption in the EID has been underestimated by approximately 60%, and doses to the maximum individual should also be recalculated. Future dose calculations should utilize an average fish consumption value of 11.3 kg/yr, and a maximum fish consumption value of 34 kg/yr

  11. Control of Grid Interactive PV Inverters for High Penetration in Low Voltage Distribution Networks

    DEFF Research Database (Denmark)

    Demirok, Erhan

    Regarding of high density deployment of PV installations in electricity grids, new technical challenges such as voltage rise, thermal loading of network components, voltage unbalance, harmonic interaction and fault current contributions are being added to tasks list of distribution system operators...... of these inverters may depend on grid connection rules which are forced by DSOs. Minimum requirement expected from PV inverters is to transfer maximum power by taking direct current (DC) form from PV modules and release it into AC grid and also continuously keep the inverters synchronized to the grid even under...... for this problem but PV inverters connected to highly capacitive networks are able to employ extra current and voltage harmonics compensation to avoid triggering network resonances at low order frequencies. The barriers such as harmonics interaction, flicker, fault current contribution and dc current injections...

  12. Technology scan of future traveler information systems and applications in Georgia.

    Science.gov (United States)

    2013-10-01

    Statewide traveler information provided in Georgia through its NaviGAtor/5-1-1 system is : primarily based on Intelligent Transportation Systems (ITS) related to freeway traffic : management. The purpose of this study is to evaluate traveler informat...

  13. Construction of phosphorylation interaction networks by text mining of full-length articles using the eFIP system.

    Science.gov (United States)

    Tudor, Catalina O; Ross, Karen E; Li, Gang; Vijay-Shanker, K; Wu, Cathy H; Arighi, Cecilia N

    2015-01-01

    Protein phosphorylation is a reversible post-translational modification where a protein kinase adds a phosphate group to a protein, potentially regulating its function, localization and/or activity. Phosphorylation can affect protein-protein interactions (PPIs), abolishing interaction with previous binding partners or enabling new interactions. Extracting phosphorylation information coupled with PPI information from the scientific literature will facilitate the creation of phosphorylation interaction networks of kinases, substrates and interacting partners, toward knowledge discovery of functional outcomes of protein phosphorylation. Increasingly, PPI databases are interested in capturing the phosphorylation state of interacting partners. We have previously developed the eFIP (Extracting Functional Impact of Phosphorylation) text mining system, which identifies phosphorylated proteins and phosphorylation-dependent PPIs. In this work, we present several enhancements for the eFIP system: (i) text mining for full-length articles from the PubMed Central open-access collection; (ii) the integration of the RLIMS-P 2.0 system for the extraction of phosphorylation events with kinase, substrate and site information; (iii) the extension of the PPI module with new trigger words/phrases describing interactions and (iv) the addition of the iSimp tool for sentence simplification to aid in the matching of syntactic patterns. We enhance the website functionality to: (i) support searches based on protein roles (kinases, substrates, interacting partners) or using keywords; (ii) link protein entities to their corresponding UniProt identifiers if mapped and (iii) support visual exploration of phosphorylation interaction networks using Cytoscape. The evaluation of eFIP on full-length articles achieved 92.4% precision, 76.5% recall and 83.7% F-measure on 100 article sections. To demonstrate eFIP for knowledge extraction and discovery, we constructed phosphorylation-dependent interaction

  14. Architecture of transcriptional regulatory circuits is knitted over the topology of bio-molecular interaction networks

    DEFF Research Database (Denmark)

    Soberano de Oliveira, Ana Paula; Patil, Kiran Raosaheb; Nielsen, Jens

    2008-01-01

    is to use the topology of bio-molecular interaction networks in order to constrain the solution space. Such approaches systematically integrate the existing biological knowledge with the 'omics' data. Results: Here we introduce a hypothesis-driven method that integrates bio-molecular network topology......Background: Uncovering the operating principles underlying cellular processes by using 'omics' data is often a difficult task due to the high-dimensionality of the solution space that spans all interactions among the bio-molecules under consideration. A rational way to overcome this problem...... with transcriptome data, thereby allowing the identification of key biological features (Reporter Features) around which transcriptional changes are significantly concentrated. We have combined transcriptome data with different biological networks in order to identify Reporter Gene Ontologies, Reporter Transcription...

  15. Interaction type influences ecological network structure more than local abiotic conditions: evidence from endophytic and endolichenic fungi at a continental scale.

    Science.gov (United States)

    Chagnon, Pierre-Luc; U'Ren, Jana M; Miadlikowska, Jolanta; Lutzoni, François; Arnold, A Elizabeth

    2016-01-01

    Understanding the factors that shape community assembly remains one of the most enduring and important questions in modern ecology. Network theory can reveal rules of community assembly within and across study systems and suggest novel hypotheses regarding the formation and stability of communities. However, such studies generally face the challenge of disentangling the relative influence of factors such as interaction type and environmental conditions on shaping communities and associated networks. Endophytic and endolichenic symbioses, characterized by microbial species that occur within healthy plants and lichen thalli, represent some of the most ubiquitous interactions in nature. Fungi that engage in these symbioses are hyperdiverse, often horizontally transmitted, and functionally beneficial in many cases, and they represent the diversification of multiple phylogenetic groups. We evaluated six measures of ecological network structure for >4100 isolates of endophytic and endolichenic fungi collected systematically from five sites across North America. Our comparison of these co-occurring interactions in biomes ranging from tundra to subtropical forest showed that the type of interactions (i.e., endophytic vs. endolichenic) had a much more pronounced influence on network structure than did environmental conditions. In particular, endophytic networks were less nested, less connected, and more modular than endolichenic networks in all sites. The consistency of the network structure within each interaction type, independent of site, is encouraging for current efforts devoted to gathering metadata on ecological network structure at a global scale. We discuss several mechanisms potentially responsible for such patterns and draw attention to knowledge gaps in our understanding of networks for diverse interaction types.

  16. Bowling alone but tweeting together: the evolution of human interaction in the social networking era

    OpenAIRE

    Antoci, Angelo; Sabatini, Fabio; Sodini, Mauro

    2011-01-01

    The objective of this paper is to theoretically analyze how human interaction may evolve in a world characterized by the explosion of online networking and other Web-mediated ways of building and nurturing relationships. The analysis shows that online networking yields a storage mechanism through which any individual contribution - e.g. a blog post, a comment, or a photo - is stored within a particular network and ready for virtual access by each member who connects to the network. When someo...

  17. Solar Data Mining at Georgia State University

    Science.gov (United States)

    Angryk, R.; Martens, P. C.; Schuh, M.; Aydin, B.; Kempton, D.; Banda, J.; Ma, R.; Naduvil-Vadukootu, S.; Akkineni, V.; Küçük, A.; Filali Boubrahimi, S.; Hamdi, S. M.

    2016-12-01

    In this talk we give an overview of research projects related to solar data analysis that are conducted at Georgia State University. We will provide update on multiple advances made by our research team on the analysis of image parameters, spatio-temporal patterns mining, temporal data analysis and our experiences with big, heterogeneous solar data visualization, analysis, processing and storage. We will talk about up-to-date data mining methodologies, and their importance for big data-driven solar physics research.

  18. Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks.

    Science.gov (United States)

    Nicosia, Vincenzo; Skardal, Per Sebastian; Arenas, Alex; Latora, Vito

    2017-03-31

    We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.

  19. Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks

    Science.gov (United States)

    Nicosia, Vincenzo; Skardal, Per Sebastian; Arenas, Alex; Latora, Vito

    2017-03-01

    We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.

  20. Cryptosporidium and Giardia in Swimming Pools, Atlanta, Georgia

    Centers for Disease Control (CDC) Podcasts

    In this podcast, Dan Rutz speaks with Dr. Joan Shields, a guest researcher with the Healthy Swimming Program at CDC, about an article in June 2008 issue of Emerging Infectious Diseases reporting on the results of a test of swimming pools in the greater Atlanta, Georgia area. Dr. Shields tested 160 pools in metro Atlanta last year for Cryptosporidium and Giardia. These germs cause most recreational water associated outbreaks.

  1. Modelling indirect interactions during failure spreading in a project activity network.

    Science.gov (United States)

    Ellinas, Christos

    2018-03-12

    Spreading broadly refers to the notion of an entity propagating throughout a networked system via its interacting components. Evidence of its ubiquity and severity can be seen in a range of phenomena, from disease epidemics to financial systemic risk. In order to understand the dynamics of these critical phenomena, computational models map the probability of propagation as a function of direct exposure, typically in the form of pairwise interactions between components. By doing so, the important role of indirect interactions remains unexplored. In response, we develop a simple model that accounts for the effect of both direct and subsequent exposure, which we deploy in the novel context of failure propagation within a real-world engineering project. We show that subsequent exposure has a significant effect in key aspects, including the: (a) final spreading event size, (b) propagation rate, and (c) spreading event structure. In addition, we demonstrate the existence of 'hidden influentials' in large-scale spreading events, and evaluate the role of direct and subsequent exposure in their emergence. Given the evidence of the importance of subsequent exposure, our findings offer new insight on particular aspects that need to be included when modelling network dynamics in general, and spreading processes specifically.

  2. Bank of Georgia jäi sõja jalgu / Romet Kreek

    Index Scriptorium Estoniae

    Kreek, Romet, 1972-

    2008-01-01

    Pinev olukord Gruusias ei ole Bank of Georgia tööd veel halvanud, kuid pikemas perspektiivis sõltub panga saatus sellest, kuidas läheb edasi Gruusia majandusel. Graafik: Aktsia oli langustrendis ammu enne Venemaa kallaletungi Gruusiale. Lisad

  3. Summary of the Georgia Agricultural Water Conservation and Metering Program and evaluation of methods used to collect and analyze irrigation data in the middle and lower Chattahoochee and Flint River basins, 2004-2010

    Science.gov (United States)

    Torak, Lynn J.; Painter, Jaime A.

    2011-01-01

    between volumes of applied irrigation derived from groundwater and surface water. Analysis of per-acre irrigation depths provided a commonality for comparing irrigation practices across the entire range of field sizes in southern Georgia and indicated underreporting of irrigated acres for some systems. Well-to-pond systems supplied irrigation at depths similar to groundwater and can be combined with groundwater irrigation data for subsequent analyses. Average irrigation depths during 2010 indicated an increase from average irrigation depths during 2008 and 2009, most likely the result of relatively dry conditions during 2010 compared to conditions in 2008 and 2009. Geostatistical models facilitated estimation of irrigation water use for unmetered systems and demonstrated usefulness in redesigning the telemetry network. Geospatial analysis evaluated the ability of the telemetry network to represent annually reported water-meter data and presented an objective, unbiased method for revising the network.

  4. bNEAT: a Bayesian network method for detecting epistatic interactions in genome-wide association studies

    Directory of Open Access Journals (Sweden)

    Chen Xue-wen

    2011-07-01

    Full Text Available Abstract Background Detecting epistatic interactions plays a significant role in improving pathogenesis, prevention, diagnosis and treatment of complex human diseases. A recent study in automatic detection of epistatic interactions shows that Markov Blanket-based methods are capable of finding genetic variants strongly associated with common diseases and reducing false positives when the number of instances is large. Unfortunately, a typical dataset from genome-wide association studies consists of very limited number of examples, where current methods including Markov Blanket-based method may perform poorly. Results To address small sample problems, we propose a Bayesian network-based approach (bNEAT to detect epistatic interactions. The proposed method also employs a Branch-and-Bound technique for learning. We apply the proposed method to simulated datasets based on four disease models and a real dataset. Experimental results show that our method outperforms Markov Blanket-based methods and other commonly-used methods, especially when the number of samples is small. Conclusions Our results show bNEAT can obtain a strong power regardless of the number of samples and is especially suitable for detecting epistatic interactions with slight or no marginal effects. The merits of the proposed approach lie in two aspects: a suitable score for Bayesian network structure learning that can reflect higher-order epistatic interactions and a heuristic Bayesian network structure learning method.

  5. Differential reconstructed gene interaction networks for deriving toxicity threshold in chemical risk assessment.

    Science.gov (United States)

    Yang, Yi; Maxwell, Andrew; Zhang, Xiaowei; Wang, Nan; Perkins, Edward J; Zhang, Chaoyang; Gong, Ping

    2013-01-01

    Pathway alterations reflected as changes in gene expression regulation and gene interaction can result from cellular exposure to toxicants. Such information is often used to elucidate toxicological modes of action. From a risk assessment perspective, alterations in biological pathways are a rich resource for setting toxicant thresholds, which may be more sensitive and mechanism-informed than traditional toxicity endpoints. Here we developed a novel differential networks (DNs) approach to connect pathway perturbation with toxicity threshold setting. Our DNs approach consists of 6 steps: time-series gene expression data collection, identification of altered genes, gene interaction network reconstruction, differential edge inference, mapping of genes with differential edges to pathways, and establishment of causal relationships between chemical concentration and perturbed pathways. A one-sample Gaussian process model and a linear regression model were used to identify genes that exhibited significant profile changes across an entire time course and between treatments, respectively. Interaction networks of differentially expressed (DE) genes were reconstructed for different treatments using a state space model and then compared to infer differential edges/interactions. DE genes possessing differential edges were mapped to biological pathways in databases such as KEGG pathways. Using the DNs approach, we analyzed a time-series Escherichia coli live cell gene expression dataset consisting of 4 treatments (control, 10, 100, 1000 mg/L naphthenic acids, NAs) and 18 time points. Through comparison of reconstructed networks and construction of differential networks, 80 genes were identified as DE genes with a significant number of differential edges, and 22 KEGG pathways were altered in a concentration-dependent manner. Some of these pathways were perturbed to a degree as high as 70% even at the lowest exposure concentration, implying a high sensitivity of our DNs approach

  6. 78 FR 45898 - Vidalia Onions Grown in Georgia; Continuance Referendum

    Science.gov (United States)

    2013-07-30

    ... Vidalia onions produced in the production area. DATES: The referendum will be conducted from September 9... through September 27, 2013, among Vidalia onion producers in the production area. Only Vidalia onion producers that were engaged in the production of Vidalia onions in Georgia during the period of January 1...

  7. Protein Annotation from Protein Interaction Networks and Gene Ontology

    OpenAIRE

    Nguyen, Cao D.; Gardiner, Katheleen J.; Cios, Krzysztof J.

    2011-01-01

    We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precis...

  8. A 3D network of helicates fully assembled by pi-stacking interactions.

    Science.gov (United States)

    Vázquez, Miguel; Taglietti, Angelo; Gatteschi, Dante; Sorace, Lorenzo; Sangregorio, Claudio; González, Ana M; Maneiro, Marcelino; Pedrido, Rosa M; Bermejo, Manuel R

    2003-08-07

    The neutral dinuclear dihelicate [Cu2(L)2] x 2CH3CN (1) forms a unique 3D network in the solid state due to pi-stacking interactions, which are responsible for intermolecular antiferromagnetic coupling between Cu(II) ions.

  9. Exploring complex miRNA-mRNA interactions with Bayesian networks by splitting-averaging strategy

    Directory of Open Access Journals (Sweden)

    Liu Lin

    2009-12-01

    Full Text Available Abstract Background microRNAs (miRNAs regulate target gene expression by controlling their mRNAs post-transcriptionally. Increasing evidence demonstrates that miRNAs play important roles in various biological processes. However, the functions and precise regulatory mechanisms of most miRNAs remain elusive. Current research suggests that miRNA regulatory modules are complicated, including up-, down-, and mix-regulation for different physiological conditions. Previous computational approaches for discovering miRNA-mRNA interactions focus only on down-regulatory modules. In this work, we present a method to capture complex miRNA-mRNA interactions including all regulatory types between miRNAs and mRNAs. Results We present a method to capture complex miRNA-mRNA interactions using Bayesian network structure learning with splitting-averaging strategy. It is designed to explore all possible miRNA-mRNA interactions by integrating miRNA-targeting information, expression profiles of miRNAs and mRNAs, and sample categories. We also present an analysis of data sets for epithelial and mesenchymal transition (EMT. Our results show that the proposed method identified all possible types of miRNA-mRNA interactions from the data. Many interactions are of tremendous biological significance. Some discoveries have been validated by previous research, for example, the miR-200 family negatively regulates ZEB1 and ZEB2 for EMT. Some are consistent with the literature, such as LOX has wide interactions with the miR-200 family members for EMT. Furthermore, many novel interactions are statistically significant and worthy of validation in the near future. Conclusions This paper presents a new method to explore the complex miRNA-mRNA interactions for different physiological conditions using Bayesian network structure learning with splitting-averaging strategy. The method makes use of heterogeneous data including miRNA-targeting information, expression profiles of miRNAs and

  10. Interrogating the architecture of protein assemblies and protein interaction networks by cross-linking mass spectrometry

    NARCIS (Netherlands)

    Liu, Fan; Heck, Albert J R

    2015-01-01

    Proteins are involved in almost all processes of the living cell. They are organized through extensive networks of interaction, by tightly bound macromolecular assemblies or more transiently via signaling nodes. Therefore, revealing the architecture of protein complexes and protein interaction

  11. On Teaching History in the Prisons of Georgia: A Person View.

    Science.gov (United States)

    Durand, Robert

    1991-01-01

    Teaches a history course in a correctional facility in Georgia. Discusses class problems, testing, grading procedures, and the environment. Finds establishing routine is effective in bringing order and purpose to the class. Describes student characteristics and response to the class. (NL)

  12. Risk Factors for Hepatitis C Virus Infection among Blood Donors in Georgia

    International Nuclear Information System (INIS)

    Zaller, Nickolas; Nelson, Kenrad E.; Aladashvili, Malvina; Badridze, Nino; Rio, Carlos del; Tsertsvadze, Tengiz

    2004-01-01

    Background: Growing awareness about the importance of blood safety for controlling the transmission of hepatitis C virus (HCV) has helped to decrease the spread of this virus in many settings. This study was conducted in order to evaluate potential risk factors for HCV infection among blood donors in Georgia. Methods: The study population consisted of 553 blood donors in three major Georgian cities; Tbilisi, the capital city and Batumi and Poti, naval port cities. Risk factors were examined using a behavior questionnaire. All blood samples were initially tested using 3rd generation anti-HCV enzyme-linked immunosorbent assays and confirmed using recombinant immunoblot assays and nucleic acid testing. Results: Forty-three blood donors, 7.8%, were confirmed HCV positive. Significant risk factors included: drug injection ever (OR: 42; 95% CI: 3.2-550.7); history of hepatitis (OR: 25.9; 95% CI: 4.6-145.5); history of a previous surgical procedure (OR: 148.4; 95% CI: 26.9-817.4); blood transfusion (OR: 25.9; 95% CI: 3.2-210.9). Conclusions: This study found a very high prevalence of HCV among blood donors in Georgia. The main risk factor for HCV infection in this population of blood donors was previous contact with contaminated blood or blood products. Reliable screening of donors and their blood is critical for controlling the further spread of HCV in Georgia

  13. A brief review of some pathology research supported by the Georgia Commodity Commission for Pecans at the USDA-ARS, Byron

    Science.gov (United States)

    With the changes currently taking place nationally in the pecan industry, and the production issues faced specifically by growers in Georgia and elsewhere in the southeastern region, the pathology research projects funded by the Georgia Commodity Commission for Pecans (CC) are reviewed. The results ...

  14. Percolation of interdependent network of networks

    International Nuclear Information System (INIS)

    Havlin, Shlomo; Stanley, H. Eugene; Bashan, Amir; Gao, Jianxi; Kenett, Dror Y.

    2015-01-01

    Complex networks appear in almost every aspect of science and technology. Previous work in network theory has focused primarily on analyzing single networks that do not interact with other networks, despite the fact that many real-world networks interact with and depend on each other. Very recently an analytical framework for studying the percolation properties of interacting networks has been introduced. Here we review the analytical framework and the results for percolation laws for a Network Of Networks (NONs) formed by n interdependent random networks. The percolation properties of a network of networks differ greatly from those of single isolated networks. In particular, because the constituent networks of a NON are connected by node dependencies, a NON is subject to cascading failure. When there is strong interdependent coupling between networks, the percolation transition is discontinuous (first-order) phase transition, unlike the well-known continuous second-order transition in single isolated networks. Moreover, although networks with broader degree distributions, e.g., scale-free networks, are more robust when analyzed as single networks, they become more vulnerable in a NON. We also review the effect of space embedding on network vulnerability. It is shown that for spatially embedded networks any finite fraction of dependency nodes will lead to abrupt transition

  15. Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human--Robot Interaction

    Directory of Open Access Journals (Sweden)

    Tatsuro Yamada

    2016-07-01

    Full Text Available To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language--behavior relationships and the temporal patterns of interaction. Here, ``internal dynamics'' refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language--behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language--behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

  16. Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human-Robot Interaction.

    Science.gov (United States)

    Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya

    2016-01-01

    To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language-behavior relationships and the temporal patterns of interaction. Here, "internal dynamics" refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language-behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language-behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

  17. Protein-Protein Interaction Article Classification Using a Convolutional Recurrent Neural Network with Pre-trained Word Embeddings.

    Science.gov (United States)

    Matos, Sérgio; Antunes, Rui

    2017-12-13

    Curation of protein interactions from scientific articles is an important task, since interaction networks are essential for the understanding of biological processes associated with disease or pharmacological action for example. However, the increase in the number of publications that potentially contain relevant information turns this into a very challenging and expensive task. In this work we used a convolutional recurrent neural network for identifying relevant articles for extracting information regarding protein interactions. Using the BioCreative III Article Classification Task dataset, we achieved an area under the precision-recall curve of 0.715 and a Matthew's correlation coefficient of 0.600, which represents an improvement over previous works.

  18. Teachers' Attitudes toward Assessment of Student Learning and Teacher Assessment Practices in General Educational Institutions: The Case of Georgia

    Science.gov (United States)

    Kitiashvili, Anastasia

    2014-01-01

    The aim of this article is to study teachers' attitudes toward assessment of students' learning and their assessment practices in Georgia's general educational institutions. Georgia is a country in the South Caucasus with a population of 4.5 million people, with 2300 general educational institutions and about 559,400 students. The research…

  19. The Protein Interaction Network of Bacteriophage Lambda with Its Host, Escherichia coli

    Science.gov (United States)

    Blasche, Sonja; Wuchty, Stefan; Rajagopala, Seesandra V.

    2013-01-01

    Although most of the 73 open reading frames (ORFs) in bacteriophage λ have been investigated intensively, the function of many genes in host-phage interactions remains poorly understood. Using yeast two-hybrid screens of all lambda ORFs for interactions with its host Escherichia coli, we determined a raw data set of 631 host-phage interactions resulting in a set of 62 high-confidence interactions after multiple rounds of retesting. These links suggest novel regulatory interactions between the E. coli transcriptional network and lambda proteins. Targeted host proteins and genes required for lambda infection are enriched among highly connected proteins, suggesting that bacteriophages resemble interaction patterns of human viruses. Lambda tail proteins interact with both bacterial fimbrial proteins and E. coli proteins homologous to other phage proteins. Lambda appears to dramatically differ from other phages, such as T7, because of its unusually large number of modified and processed proteins, which reduces the number of host-virus interactions detectable by yeast two-hybrid screens. PMID:24049175

  20. A value orientation approach to assess and compare climate change risk perception among trout anglers in Georgia, USA

    Science.gov (United States)

    Ramesh Paudyal; Neelam C. Poudyal; J.M. Bowker; Adrienne M. Dorison; Stanley J. Zarnoch; Gary T. Green

    2015-01-01

    Trout in Georgia could experience early impacts from climate change as the streams in the region are located at the southern most edge of their North American home range. This study surveyed trout anglers in Georgia to understand how anglers perceive the potential impact of climate change on trout, and whether and how their perception and response to declines in trout...