Network analysis of epidermal growth factor signaling using integrated genomic, proteomic and phosphorylation data.

Directory of Open Access Journals (Sweden)

Katrina M Waters

Full Text Available To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.

Network Analysis of Epidermal Growth Factor Signaling using Integrated Genomic, Proteomic and Phosphorylation Data

Energy Technology Data Exchange (ETDEWEB)

Waters, Katrina M.; Liu, Tao; Quesenberry, Ryan D.; Willse, Alan R.; Bandyopadhyay, Somnath; Kathmann, Loel E.; Weber, Thomas J.; Smith, Richard D.; Wiley, H. S.; Thrall, Brian D.

2012-03-29

To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods

Science.gov (United States)

Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E.; Re, Matteo

2014-01-01

Objective In the context of “network medicine”, gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. Materials and methods We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. Results The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different “informativeness” embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Conclusions Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further

NASA Integrated Network COOP

Science.gov (United States)

Anderson, Michael L.; Wright, Nathaniel; Tai, Wallace

2012-01-01

Natural disasters, terrorist attacks, civil unrest, and other events have the potential of disrupting mission-essential operations in any space communications network. NASA's Space Communications and Navigation office (SCaN) is in the process of studying options for integrating the three existing NASA network elements, the Deep Space Network, the Near Earth Network, and the Space Network, into a single integrated network with common services and interfaces. The need to maintain Continuity of Operations (COOP) after a disastrous event has a direct impact on the future network design and operations concepts. The SCaN Integrated Network will provide support to a variety of user missions. The missions have diverse requirements and include anything from earth based platforms to planetary missions and rovers. It is presumed that an integrated network, with common interfaces and processes, provides an inherent advantage to COOP in that multiple elements and networks can provide cross-support in a seamless manner. The results of trade studies support this assumption but also show that centralization as a means of achieving integration can result in single points of failure that must be mitigated. The cost to provide this mitigation can be substantial. In support of this effort, the team evaluated the current approaches to COOP, developed multiple potential approaches to COOP in a future integrated network, evaluated the interdependencies of the various approaches to the various network control and operations options, and did a best value assessment of the options. The paper will describe the trade space, the study methods, and results of the study.

Analysis of thevenin equivalent network of a distribution system for solar integration studies

DEFF Research Database (Denmark)

Yang, Guangya; Mattesen, Majken; Kjaer, Søren Bækhøj

2012-01-01

generations and expected to play a significant role in the future sustainable energy system. Currently one of the main issues for solar integration is the voltage regulation problem in the LV grid, as to the small X/R ratios. Hence, the voltage control techniques developed for the MV and HV networks may need...... to be further evaluated before applied for the LV grid. For the inverter voltage control design, it is useful to develop a realistic Thevenin equivalent model for the grid to ease the analysis. In this paper, case studies are performed based on the analysis of a realistic distribution network for the design...

Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios

Science.gov (United States)

Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

2015-01-01

This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN. PMID:26593919

Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios.

Science.gov (United States)

Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

2015-11-17

This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.

Science.gov (United States)

Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E; Re, Matteo

2014-06-01

In the context of "network medicine", gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different "informativeness" embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further enhance disease gene ranking results, by adopting both

Tools and Models for Integrating Multiple Cellular Networks

Energy Technology Data Exchange (ETDEWEB)

Gerstein, Mark [Yale Univ., New Haven, CT (United States). Gerstein Lab.

2015-11-06

In this grant, we have systematically investigated the integrated networks, which are responsible for the coordination of activity between metabolic pathways in prokaryotes. We have developed several computational tools to analyze the topology of the integrated networks consisting of metabolic, regulatory, and physical interaction networks. The tools are all open-source, and they are available to download from Github, and can be incorporated in the Knowledgebase. Here, we summarize our work as follow. Understanding the topology of the integrated networks is the first step toward understanding its dynamics and evolution. For Aim 1 of this grant, we have developed a novel algorithm to determine and measure the hierarchical structure of transcriptional regulatory networks [1]. The hierarchy captures the direction of information flow in the network. The algorithm is generally applicable to regulatory networks in prokaryotes, yeast and higher organisms. Integrated datasets are extremely beneficial in understanding the biology of a system in a compact manner due to the conflation of multiple layers of information. Therefore for Aim 2 of this grant, we have developed several tools and carried out analysis for integrating system-wide genomic information. To make use of the structural data, we have developed DynaSIN for protein-protein interactions networks with various dynamical interfaces [2]. We then examined the association between network topology with phenotypic effects such as gene essentiality. In particular, we have organized E. coli and S. cerevisiae transcriptional regulatory networks into hierarchies. We then correlated gene phenotypic effects by tinkering with different layers to elucidate which layers were more tolerant to perturbations [3]. In the context of evolution, we also developed a workflow to guide the comparison between different types of biological networks across various species using the concept of rewiring [4], and Furthermore, we have developed

Machine-to-Machine networks: integration of M2M networks into companies' administrative networks

OpenAIRE

Pointereau, Romain

2013-01-01

This analysis will address the technical, economic and regulatory aspects and will identify the position taken by the various market actors. Integration of M2M Networks into Companies' Administrative Networks. Integración de redes M2M en redes administrativas de las empresas. Integració de xarxes M2M en xarxes administratives de les empreses.

UMA/GAN network architecture analysis

Science.gov (United States)

Yang, Liang; Li, Wensheng; Deng, Chunjian; Lv, Yi

2009-07-01

This paper is to critically analyze the architecture of UMA which is one of Fix Mobile Convergence (FMC) solutions, and also included by the third generation partnership project(3GPP). In UMA/GAN network architecture, UMA Network Controller (UNC) is the key equipment which connects with cellular core network and mobile station (MS). UMA network could be easily integrated into the existing cellular networks without influencing mobile core network, and could provides high-quality mobile services with preferentially priced indoor voice and data usage. This helps to improve subscriber's experience. On the other hand, UMA/GAN architecture helps to integrate other radio technique into cellular network which includes WiFi, Bluetooth, and WiMax and so on. This offers the traditional mobile operators an opportunity to integrate WiMax technique into cellular network. In the end of this article, we also give an analysis of potential influence on the cellular core networks ,which is pulled by UMA network.

Network-assisted crop systems genetics: network inference and integrative analysis.

Science.gov (United States)

Lee, Tak; Kim, Hyojin; Lee, Insuk

2015-04-01

Although next-generation sequencing (NGS) technology has enabled the decoding of many crop species genomes, most of the underlying genetic components for economically important crop traits remain to be determined. Network approaches have proven useful for the study of the reference plant, Arabidopsis thaliana, and the success of network-based crop genetics will also require the availability of a genome-scale functional networks for crop species. In this review, we discuss how to construct functional networks and elucidate the holistic view of a crop system. The crop gene network then can be used for gene prioritization and the analysis of resequencing-based genome-wide association study (GWAS) data, the amount of which will rapidly grow in the field of crop science in the coming years. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of Basic Transmission Networks for Integrated Ship Control Systems

DEFF Research Database (Denmark)

Hansen, T.N.; Granum-Jensen, M.

1993-01-01

Description of a computer network for Integrated Ship Control Systems which is going to be developed as part of an EC-project. Today equipment of different make are not able to communicate with each other because most often each supplier of ISC systems has got their own proprietary network.....

Measuring the degree of integration for an integrated service network

Directory of Open Access Journals (Sweden)

Chenglin Ye

2012-09-01

Full Text Available Background: Integration involves the coordination of services provided by autonomous agencies and improves the organization and delivery of multiple services for target patients. Current measures generally do not distinguish between agencies' perception and expectation. We propose a method for quantifying the agencies' service integration. Using the data from the Children's Treatment Network (CTN, we aimed to measure the degree of integration for the CTN agencies in York and Simcoe.  Theory and Methods: We quantified the integration by the agreement between perceived and expected levels of involvement and calculated four scores from different perspectives for each agency. We used the average score to measure the global network integration and examined the sensitivity of the global score.  Results: Most agencies' integration scores were less than 65%. As measured by the agreement between every other agency's perception and expectation, the overall integration of CTN in Simcoe and York was 44% (95% CI: 39% - 49% and 52% (95% CI: 48% - 56%, respectively. The sensitivity analysis showed that the global scores were robust.  Conclusion: Our method extends existing measures of integration and possesses a good extent of validity. We can also apply the method in monitoring improvement and linking integration with other outcomes.

Measuring the degree of integration for an integrated service network

Directory of Open Access Journals (Sweden)

Chenglin Ye

2012-09-01

Full Text Available Background: Integration involves the coordination of services provided by autonomous agencies and improves the organization and delivery of multiple services for target patients. Current measures generally do not distinguish between agencies' perception and expectation. We propose a method for quantifying the agencies' service integration. Using the data from the Children's Treatment Network (CTN, we aimed to measure the degree of integration for the CTN agencies in York and Simcoe. Theory and Methods: We quantified the integration by the agreement between perceived and expected levels of involvement and calculated four scores from different perspectives for each agency. We used the average score to measure the global network integration and examined the sensitivity of the global score. Results: Most agencies' integration scores were less than 65%. As measured by the agreement between every other agency's perception and expectation, the overall integration of CTN in Simcoe and York was 44% (95% CI: 39% - 49% and 52% (95% CI: 48% - 56%, respectively. The sensitivity analysis showed that the global scores were robust. Conclusion: Our method extends existing measures of integration and possesses a good extent of validity. We can also apply the method in monitoring improvement and linking integration with other outcomes. 

Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation.

Science.gov (United States)

Kwak, Doyeon; Kim, Wonjoon

2017-01-01

It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks.

Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation.

Directory of Open Access Journals (Sweden)

Doyeon Kwak

Full Text Available It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks.

Integrated analysis of multiple data sources reveals modular structure of biological networks

International Nuclear Information System (INIS)

Lu Hongchao; Shi Baochen; Wu Gaowei; Zhang Yong; Zhu Xiaopeng; Zhang Zhihua; Liu Changning; Zhao, Yi; Wu Tao; Wang Jie; Chen Runsheng

2006-01-01

It has been a challenging task to integrate high-throughput data into investigations of the systematic and dynamic organization of biological networks. Here, we presented a simple hierarchical clustering algorithm that goes a long way to achieve this aim. Our method effectively reveals the modular structure of the yeast protein-protein interaction network and distinguishes protein complexes from functional modules by integrating high-throughput protein-protein interaction data with the added subcellular localization and expression profile data. Furthermore, we take advantage of the detected modules to provide a reliably functional context for the uncharacterized components within modules. On the other hand, the integration of various protein-protein association information makes our method robust to false-positives, especially for derived protein complexes. More importantly, this simple method can be extended naturally to other types of data fusion and provides a framework for the study of more comprehensive properties of the biological network and other forms of complex networks

BiologicalNetworks 2.0 - an integrative view of genome biology data

Directory of Open Access Journals (Sweden)

Ponomarenko Julia

2010-12-01

Full Text Available Abstract Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other and their relations (interactions, co-expression, co-citations, and other. The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org.

Performance Analysis of Hierarchical Group Key Management Integrated with Adaptive Intrusion Detection in Mobile ad hoc Networks

Science.gov (United States)

2016-04-05

applications in wireless networks such as military battlefields, emergency response, mobile commerce , online gaming, and collaborative work are based on the...www.elsevier.com/locate/peva Performance analysis of hierarchical group key management integrated with adaptive intrusion detection in mobile ad hoc...Accepted 19 September 2010 Available online 26 September 2010 Keywords: Mobile ad hoc networks Intrusion detection Group communication systems Group

Functional brain networks underlying detection and integration of disconfirmatory evidence.

Science.gov (United States)

Lavigne, Katie M; Metzak, Paul D; Woodward, Todd S

2015-05-15

Processing evidence that disconfirms a prior interpretation is a fundamental aspect of belief revision, and has clear social and clinical relevance. This complex cognitive process requires (at minimum) an alerting stage and an integration stage, and in the current functional magnetic resonance imaging (fMRI) study, we used multivariate analysis methodology on two datasets in an attempt to separate these sequentially-activated cognitive stages and link them to distinct functional brain networks. Thirty-nine healthy participants completed one of two versions of an evidence integration experiment involving rating two consecutive animal images, both of which consisted of two intact images of animal faces morphed together at different ratios (e.g., 70/30 bird/dolphin followed by 10/90 bird/dolphin). The two versions of the experiment differed primarily in terms of stimulus presentation and timing, which facilitated functional interpretation of brain networks based on differences in the hemodynamic response shapes between versions. The data were analyzed using constrained principal component analysis for fMRI (fMRI-CPCA), which allows distinct, simultaneously active task-based networks to be separated, and these were interpreted using both temporal (task-based hemodynamic response shapes) and spatial (dominant brain regions) information. Three networks showed increased activity during integration of disconfirmatory relative to confirmatory evidence: (1) a network involved in alerting to the requirement to revise an interpretation, identified as the salience network (dorsal anterior cingulate cortex and bilateral insula); (2) a sensorimotor response-related network (pre- and post-central gyri, supplementary motor area, and thalamus); and (3) an integration network involving rostral prefrontal, orbitofrontal and posterior parietal cortex. These three networks were staggered in their peak activity (alerting, responding, then integrating), but at certain time points (e

Network Analysis Tools: from biological networks to clusters and pathways.

Science.gov (United States)

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

2008-01-01

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

Integrated Analysis of Environment-driven Operational Effects in Sensor Networks

Energy Technology Data Exchange (ETDEWEB)

Park, Alfred J [ORNL; Perumalla, Kalyan S [ORNL

2007-07-01

There is a rapidly growing need to evaluate sensor network functionality and performance in the context of the larger environment of infrastructure and applications in which the sensor network is organically embedded. This need, which is motivated by complex applications related to national security operations, leads to a paradigm fundamentally different from that of traditional data networks. In the sensor networks of interest to us, the network dynamics depend strongly on sensor activity, which in turn is triggered by events in the environment. Because the behavior of sensor networks is sensitive to these driving phenomena, the integrity of the sensed observations, measurements and resource usage by the network can widely vary. It is therefore imperative to accurately capture the environmental phenomena, and drive the simulation of the sensor network operation by accounting fully for the environment effects. In this paper, we illustrate the strong, intimate coupling between the sensor network operation and the driving phenomena in their applications with an example sensor network designed to detect and track gaseous plumes.

Brain network of semantic integration in sentence reading: insights from independent component analysis and graph theoretical analysis.

Science.gov (United States)

Ye, Zheng; Doñamayor, Nuria; Münte, Thomas F

2014-02-01

A set of cortical and sub-cortical brain structures has been linked with sentence-level semantic processes. However, it remains unclear how these brain regions are organized to support the semantic integration of a word into sentential context. To look into this issue, we conducted a functional magnetic resonance imaging (fMRI) study that required participants to silently read sentences with semantically congruent or incongruent endings and analyzed the network properties of the brain with two approaches, independent component analysis (ICA) and graph theoretical analysis (GTA). The GTA suggested that the whole-brain network is topologically stable across conditions. The ICA revealed a network comprising the supplementary motor area (SMA), left inferior frontal gyrus, left middle temporal gyrus, left caudate nucleus, and left angular gyrus, which was modulated by the incongruity of sentence ending. Furthermore, the GTA specified that the connections between the left SMA and left caudate nucleus as well as that between the left caudate nucleus and right thalamus were stronger in response to incongruent vs. congruent endings. Copyright © 2012 Wiley Periodicals, Inc.

Strategic Integration of Multiple Bioinformatics Resources for System Level Analysis of Biological Networks.

Science.gov (United States)

D'Souza, Mark; Sulakhe, Dinanath; Wang, Sheng; Xie, Bing; Hashemifar, Somaye; Taylor, Andrew; Dubchak, Inna; Conrad Gilliam, T; Maltsev, Natalia

2017-01-01

Recent technological advances in genomics allow the production of biological data at unprecedented tera- and petabyte scales. Efficient mining of these vast and complex datasets for the needs of biomedical research critically depends on a seamless integration of the clinical, genomic, and experimental information with prior knowledge about genotype-phenotype relationships. Such experimental data accumulated in publicly available databases should be accessible to a variety of algorithms and analytical pipelines that drive computational analysis and data mining.We present an integrated computational platform Lynx (Sulakhe et al., Nucleic Acids Res 44:D882-D887, 2016) ( http://lynx.cri.uchicago.edu ), a web-based database and knowledge extraction engine. It provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization. It gives public access to the Lynx integrated knowledge base (LynxKB) and its analytical tools via user-friendly web services and interfaces. The Lynx service-oriented architecture supports annotation and analysis of high-throughput experimental data. Lynx tools assist the user in extracting meaningful knowledge from LynxKB and experimental data, and in the generation of weighted hypotheses regarding the genes and molecular mechanisms contributing to human phenotypes or conditions of interest. The goal of this integrated platform is to support the end-to-end analytical needs of various translational projects.

Integration and analysis of neighbor discovery and link quality estimation in wireless sensor networks.

Science.gov (United States)

Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Abd Razak, Shukor

2014-01-01

Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications.

Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Marjan Radi

2014-01-01

Full Text Available Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications.

State-related functional integration and functional segregation brain networks in schizophrenia.

Science.gov (United States)

Yu, Qingbao; Sui, Jing; Kiehl, Kent A; Pearlson, Godfrey; Calhoun, Vince D

2013-11-01

Altered topological properties of brain connectivity networks have emerged as important features of schizophrenia. The aim of this study was to investigate how the state-related modulations to graph measures of functional integration and functional segregation brain networks are disrupted in schizophrenia. Firstly, resting state and auditory oddball discrimination (AOD) fMRI data of healthy controls (HCs) and schizophrenia patients (SZs) were decomposed into spatially independent components (ICs) by group independent component analysis (ICA). Then, weighted positive and negative functional integration (inter-component networks) and functional segregation (intra-component networks) brain networks were built in each subject. Subsequently, connectivity strength, clustering coefficient, and global efficiency of all brain networks were statistically compared between groups (HCs and SZs) in each state and between states (rest and AOD) within group. We found that graph measures of negative functional integration brain network and several positive functional segregation brain networks were altered in schizophrenia during AOD task. The metrics of positive functional integration brain network and one positive functional segregation brain network were higher during the resting state than during the AOD task only in HCs. These findings imply that state-related characteristics of both functional integration and functional segregation brain networks are impaired in schizophrenia which provides new insight into the altered brain performance in this brain disorder. © 2013.

Integrative network analysis unveils convergent molecular pathways in Parkinson's disease and diabetes.

Directory of Open Access Journals (Sweden)

Jose A Santiago

Full Text Available Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level.Using a random walk algorithm within the human functional linkage network we identified a molecular cluster of 478 neighboring genes closely associated with confirmed Parkinson's disease and type 2 diabetes genes. Biological and functional analysis identified the protein serine-threonine kinase activity, MAPK cascade, activation of the immune response, and insulin receptor and lipid signaling as convergent pathways. Integration of results from microarrays studies identified a blood signature comprising seven genes whose expression is dysregulated in Parkinson's disease and type 2 diabetes. Among this group of genes, is the amyloid precursor protein (APP, previously associated with neurodegeneration and insulin regulation. Quantification of RNA from whole blood of 192 samples from two independent clinical trials, the Harvard Biomarker Study (HBS and the Prognostic Biomarker Study (PROBE, revealed that expression of APP is significantly upregulated in Parkinson's disease patients compared to healthy controls. Assessment of biomarker performance revealed that expression of APP could distinguish Parkinson's disease from healthy individuals with a diagnostic accuracy of 80% in both cohorts of patients.These results provide the first evidence that Parkinson's disease and diabetes are strongly linked at the molecular level and that shared molecular networks provide an additional source for identifying highly sensitive biomarkers. Further, these results suggest for the first

Integrative network analysis unveils convergent molecular pathways in Parkinson's disease and diabetes.

Science.gov (United States)

Santiago, Jose A; Potashkin, Judith A

2013-01-01

Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level. Using a random walk algorithm within the human functional linkage network we identified a molecular cluster of 478 neighboring genes closely associated with confirmed Parkinson's disease and type 2 diabetes genes. Biological and functional analysis identified the protein serine-threonine kinase activity, MAPK cascade, activation of the immune response, and insulin receptor and lipid signaling as convergent pathways. Integration of results from microarrays studies identified a blood signature comprising seven genes whose expression is dysregulated in Parkinson's disease and type 2 diabetes. Among this group of genes, is the amyloid precursor protein (APP), previously associated with neurodegeneration and insulin regulation. Quantification of RNA from whole blood of 192 samples from two independent clinical trials, the Harvard Biomarker Study (HBS) and the Prognostic Biomarker Study (PROBE), revealed that expression of APP is significantly upregulated in Parkinson's disease patients compared to healthy controls. Assessment of biomarker performance revealed that expression of APP could distinguish Parkinson's disease from healthy individuals with a diagnostic accuracy of 80% in both cohorts of patients. These results provide the first evidence that Parkinson's disease and diabetes are strongly linked at the molecular level and that shared molecular networks provide an additional source for identifying highly sensitive biomarkers. Further, these results suggest for the first time that

Ontology-supported research on vaccine efficacy, safety and integrative biological networks.

Science.gov (United States)

He, Yongqun

2014-07-01

While vaccine efficacy and safety research has dramatically progressed with the methods of in silico prediction and data mining, many challenges still exist. A formal ontology is a human- and computer-interpretable set of terms and relations that represent entities in a specific domain and how these terms relate to each other. Several community-based ontologies (including Vaccine Ontology, Ontology of Adverse Events and Ontology of Vaccine Adverse Events) have been developed to support vaccine and adverse event representation, classification, data integration, literature mining of host-vaccine interaction networks, and analysis of vaccine adverse events. The author further proposes minimal vaccine information standards and their ontology representations, ontology-based linked open vaccine data and meta-analysis, an integrative One Network ('OneNet') Theory of Life, and ontology-based approaches to study and apply the OneNet theory. In the Big Data era, these proposed strategies provide a novel framework for advanced data integration and analysis of fundamental biological networks including vaccine immune mechanisms.

End-to-End Traffic Flow Modeling of the Integrated SCaN Network

Science.gov (United States)

Cheung, K.-M.; Abraham, D. S.

2012-05-01

In this article, we describe the analysis and simulation effort of the end-to-end traffic flow for the Integrated Space Communications and Navigation (SCaN) Network. Using the network traffic derived for the 30-day period of July 2018 from the Space Communications Mission Model (SCMM), we generate the wide-area network (WAN) bandwidths of the ground links for different architecture options of the Integrated SCaN Network. We also develop a new analytical scheme to model the traffic flow and buffering mechanism of a store-and-forward network. It is found that the WAN bandwidth of the Integrated SCaN Network is an important differentiator of different architecture options, as the recurring circuit costs of certain architecture options can be prohibitively high.

Thermal photovoltaic solar integrated system analysis using neural networks

Energy Technology Data Exchange (ETDEWEB)

Ashhab, S. [Hashemite Univ., Zarqa (Jordan). Dept. of Mechanical Engineering

2007-07-01

The energy demand in Jordan is primarily met by petroleum products. As such, the development of renewable energy systems is quite attractive. In particular, solar energy is a promising renewable energy source in Jordan and has been used for food canning, paper production, air-conditioning and sterilization. Artificial neural networks (ANNs) have received significant attention due to their capabilities in forecasting, modelling of complex nonlinear systems and control. ANNs have been used for forecasting solar energy. This paper presented a study that examined a thermal photovoltaic solar integrated system that was built in Jordan. Historical input-output system data that was collected experimentally was used to train an ANN that predicted the collector, PV module, pump and total efficiencies. The model predicted the efficiencies well and can therefore be utilized to find the operating conditions of the system that will produce the maximum system efficiencies. The paper provided a description of the photovoltaic solar system including equations for PV module efficiency; pump efficiency; and total efficiency. The paper also presented data relevant to the system performance and neural networks. The results of a neural net model were also presented based on the thermal PV solar integrated system data that was collected. It was concluded that the neural net model of the thermal photovoltaic solar integrated system set the background for achieving the best system performance. 10 refs., 6 figs.

Statistical analysis of network data with R

CERN Document Server

Kolaczyk, Eric D

2014-01-01

Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).

Network Based Integrated Analysis of Phenotype-Genotype Data for Prioritization of Candidate Symptom Genes

Directory of Open Access Journals (Sweden)

Xing Li

2014-01-01

Full Text Available Background. Symptoms and signs (symptoms in brief are the essential clinical manifestations for individualized diagnosis and treatment in traditional Chinese medicine (TCM. To gain insights into the molecular mechanism of symptoms, we develop a computational approach to identify the candidate genes of symptoms. Methods. This paper presents a network-based approach for the integrated analysis of multiple phenotype-genotype data sources and the prediction of the prioritizing genes for the associated symptoms. The method first calculates the similarities between symptoms and diseases based on the symptom-disease relationships retrieved from the PubMed bibliographic database. Then the disease-gene associations and protein-protein interactions are utilized to construct a phenotype-genotype network. The PRINCE algorithm is finally used to rank the potential genes for the associated symptoms. Results. The proposed method gets reliable gene rank list with AUC (area under curve 0.616 in classification. Some novel genes like CALCA, ESR1, and MTHFR were predicted to be associated with headache symptoms, which are not recorded in the benchmark data set, but have been reported in recent published literatures. Conclusions. Our study demonstrated that by integrating phenotype-genotype relationships into a complex network framework it provides an effective approach to identify candidate genes of symptoms.

Data Farming Process and Initial Network Analysis Capabilities

Directory of Open Access Journals (Sweden)

Gary Horne

2016-01-01

Full Text Available Data Farming, network applications and approaches to integrate network analysis and processes to the data farming paradigm are presented as approaches to address complex system questions. Data Farming is a quantified approach that examines questions in large possibility spaces using modeling and simulation. It evaluates whole landscapes of outcomes to draw insights from outcome distributions and outliers. Social network analysis and graph theory are widely used techniques for the evaluation of social systems. Incorporation of these techniques into the data farming process provides analysts examining complex systems with a powerful new suite of tools for more fully exploring and understanding the effect of interactions in complex systems. The integration of network analysis with data farming techniques provides modelers with the capability to gain insight into the effect of network attributes, whether the network is explicitly defined or emergent, on the breadth of the model outcome space and the effect of model inputs on the resultant network statistics.

Topology design and performance analysis of an integrated communication network

Science.gov (United States)

Li, V. O. K.; Lam, Y. F.; Hou, T. C.; Yuen, J. H.

1985-01-01

A research study on the topology design and performance analysis for the Space Station Information System (SSIS) network is conducted. It is begun with a survey of existing research efforts in network topology design. Then a new approach for topology design is presented. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. The algorithm for generating subsets is described in detail, and various aspects of the overall design procedure are discussed. Two more efficient versions of this algorithm (applicable in specific situations) are also given. Next, two important aspects of network performance analysis: network reliability and message delays are discussed. A new model is introduced to study the reliability of a network with dependent failures. For message delays, a collection of formulas from existing research results is given to compute or estimate the delays of messages in a communication network without making the independence assumption. The design algorithm coded in PASCAL is included as an appendix.

Towards the integration of social network analysis in an inter-organizational networks perspective

DEFF Research Database (Denmark)

Bergenholtz, Carsten; Waldstrøm, Christian

This conceptual paper deals with the issue of studying inter-organizational networks while applying social network analysis (SNA). SNA is a widely recognized technique in network research, particularly within intra-organizational settings, while there seems to be a significant gap in the inter......-organizational setting. Based on a literature review of both SNA as a methodology and/or theory and the field of inter-organizational networks, the aim is to gain an overview in order to provide a clear setting for SNA in inter-organizational research....

Challenges of Integrating NASA's Space Communications Networks

Science.gov (United States)

Reinert, Jessica; Barnes, Patrick

2013-01-01

The transition to new technology, innovative ideas, and resistance to change is something that every industry experiences. Recent examples of this shift are changing to using robots in the assembly line construction of automobiles or the increasing use of robotics for medical procedures. Most often this is done with cost-reduction in mind, though ease of use for the customer is also a driver. All industries experience the push to increase efficiency of their systems; National Aeronautics and Space Administration (NASA) and the commercial space industry are no different. NASA space communication services are provided by three separately designed, developed, maintained, and operated communications networks known as the Deep Space Network (DSN), Near Earth Network (NEN) and Space Network (SN). The Space Communications and Navigation (SCaN) Program is pursuing integration of these networks and has performed a variety of architecture trade studies to determine what integration options would be the most effective in achieving a unified user mission support organization, and increase the use of common operational equipment and processes. The integration of multiple, legacy organizations and existing systems has challenges ranging from technical to cultural. The existing networks are the progeny of the very first communication and tracking capabilities implemented by NASA and the Jet Propulsion Laboratory (JPL) more than 50 years ago and have been customized to the needs of their respective user mission base. The technical challenges to integrating the networks are many, though not impossible to overcome. The three distinct networks provide the same types of services, with customizable data rates, bandwidth, frequencies, and so forth. The differences across the networks have occurred in effort to satisfy their user missions' needs. Each new requirement has made the networks more unique and harder to integrate. The cultural challenges, however, have proven to be a

Challenges of Integrating NASAs Space Communication Networks

Science.gov (United States)

Reinert, Jessica M.; Barnes, Patrick

2013-01-01

The transition to new technology, innovative ideas, and resistance to change is something that every industry experiences. Recent examples of this shift are changing to using robots in the assembly line construction of automobiles or the increasing use of robotics for medical procedures. Most often this is done with cost-reduction in mind, though ease of use for the customer is also a driver. All industries experience the push to increase efficiency of their systems; National Aeronautics and Space Administration (NASA) and the commercial space industry are no different. NASA space communication services are provided by three separately designed, developed, maintained, and operated communications networks known as the Deep Space Network (DSN), Near Earth Network (NEN) and Space Network (SN). The Space Communications and Navigation (SCaN) Program is pursuing integration of these networks and has performed a variety of architecture trade studies to determine what integration options would be the most effective in achieving a unified user mission support organization, and increase the use of common operational equipment and processes. The integration of multiple, legacy organizations and existing systems has challenges ranging from technical to cultural. The existing networks are the progeny of the very first communication and tracking capabilities implemented by NASA and the Jet Propulsion Laboratory (JPL) more than 50 years ago and have been customized to the needs of their respective user mission base. The technical challenges to integrating the networks are many, though not impossible to overcome. The three distinct networks provide the same types of services, with customizable data rates, bandwidth, frequencies, and so forth. The differences across the networks have occurred in effort to satisfy their user missions' needs. Each new requirement has made the networks more unique and harder to integrate. The cultural challenges, however, have proven to be a

Integration of RFID and Wireless Sensor Networks

Institute of Scientific and Technical Information of China (English)

Miodrag; Bolic; Amiya; Nayak; Ivan; Stojmenovi.

2007-01-01

Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) are two important wireless technologies that have wide variety of applications and provide limitless future potentials. However,RFID and sensor networks almost are under development in parallel way. Integration of RFID and wireless sensor networks attracts little attention from research community. This paper first presents a brief introduction on RFID,and then investigates recent research works,new products/patents and applications that integrate RFID with sensor networks. Four types of integration are discussed. They are integrating tags with sensors,integrating tags with wireless sensor nodes,integrating readers with wireless sensor nodes and wire-less devices,and mix of RFID and sensors. New challenges and future works are discussed in the end.

Integration opportunities for HIV and family planning services in Addis Ababa, Ethiopia: an organizational network analysis.

Science.gov (United States)

Thomas, James C; Reynolds, Heidi; Bevc, Christine; Tsegaye, Ademe

2014-01-18

Public health resources are often deployed in developing countries by foreign governments, national governments, civil society and the private health clinics, but seldom in ways that are coordinated within a particular community or population. The lack of coordination results in inefficiencies and suboptimal results. Organizational network analysis can reveal how organizations interact with each other and provide insights into means of realizing better public health results from the resources already deployed. Our objective in this study was to identify the missed opportunities for the integration of HIV care and family planning services and to inform future network strengthening. In two sub-cities of Addis Ababa, we identified each organization providing either HIV care or family planning services. We interviewed representatives of each of them about exchanges of clients with each of the others. With network analysis, we identified network characteristics in each sub-city network, such as referral density and centrality; and gaps in the referral patterns. The results were shared with representatives from the organizations. The two networks were of similar size (25 and 26 organizations) and had referral densities of 0.115 and 0.155 out of a possible range from 0 (none) to 1.0 (all possible connections). Two organizations in one sub-city did not refer HIV clients to a family planning organization. One organization in one sub-city and seven in the other offered few HIV services and did not refer clients to any other HIV service provider. Representatives from the networks confirmed the results reflected their experience and expressed an interest in establishing more links between organizations. Because of organizations not working together, women in the two sub-cities were at risk of not receiving needed family planning or HIV care services. Facilitating referrals among a few organizations that are most often working in isolation could remediate the problem, but the

Social network analysis and supply chain management

Directory of Open Access Journals (Sweden)

Raúl Rodríguez Rodríguez

2016-01-01

Full Text Available This paper deals with social network analysis and how it could be integrated within supply chain management from a decision-making point of view. Even though the benefits of using social analysis have are widely accepted at both academic and industry/services context, there is still a lack of solid frameworks that allow decision-makers to connect the usage and obtained results of social network analysis – mainly both information and knowledge flows and derived results- with supply chain management objectives and goals. This paper gives an overview of social network analysis, the main social network analysis metrics, supply chain performance and, finally, it identifies how future frameworks could close the gap and link the results of social network analysis with the supply chain management decision-making processes.

Differential neural network configuration during human path integration

Science.gov (United States)

Arnold, Aiden E. G. F; Burles, Ford; Bray, Signe; Levy, Richard M.; Iaria, Giuseppe

2014-01-01

Path integration is a fundamental skill for navigation in both humans and animals. Despite recent advances in unraveling the neural basis of path integration in animal models, relatively little is known about how path integration operates at a neural level in humans. Previous attempts to characterize the neural mechanisms used by humans to visually path integrate have suggested a central role of the hippocampus in allowing accurate performance, broadly resembling results from animal data. However, in recent years both the central role of the hippocampus and the perspective that animals and humans share similar neural mechanisms for path integration has come into question. The present study uses a data driven analysis to investigate the neural systems engaged during visual path integration in humans, allowing for an unbiased estimate of neural activity across the entire brain. Our results suggest that humans employ common task control, attention and spatial working memory systems across a frontoparietal network during path integration. However, individuals differed in how these systems are configured into functional networks. High performing individuals were found to more broadly express spatial working memory systems in prefrontal cortex, while low performing individuals engaged an allocentric memory system based primarily in the medial occipito-temporal region. These findings suggest that visual path integration in humans over short distances can operate through a spatial working memory system engaging primarily the prefrontal cortex and that the differential configuration of memory systems recruited by task control networks may help explain individual biases in spatial learning strategies. PMID:24808849

Review Essay: Does Qualitative Network Analysis Exist?

Directory of Open Access Journals (Sweden)

Rainer Diaz-Bone

2007-01-01

Full Text Available Social network analysis was formed and established in the 1970s as a way of analyzing systems of social relations. In this review the theoretical-methodological standpoint of social network analysis ("structural analysis" is introduced and the different forms of social network analysis are presented. Structural analysis argues that social actors and social relations are embedded in social networks, meaning that action and perception of actors as well as the performance of social relations are influenced by the network structure. Since the 1990s structural analysis has integrated concepts such as agency, discourse and symbolic orientation and in this way structural analysis has opened itself. Since then there has been increasing use of qualitative methods in network analysis. They are used to include the perspective of the analyzed actors, to explore networks, and to understand network dynamics. In the reviewed book, edited by Betina HOLLSTEIN and Florian STRAUS, the twenty predominantly empirically orientated contributions demonstrate the possibilities of combining quantitative and qualitative methods in network analyses in different research fields. In this review we examine how the contributions succeed in applying and developing the structural analysis perspective, and the self-positioning of "qualitative network analysis" is evaluated. URN: urn:nbn:de:0114-fqs0701287

European networks in structural integrity

International Nuclear Information System (INIS)

Crutzen, S.; Davies, M.; Hemsworth, B.; Hurst, R.; Kussmaul, K.

1994-01-01

Several institutions and electrical utilities in Europe, including the Joint Research Centre (JRC) have the capability to deal problems posed by the operation and ageing of structural components and with their structural integrity assessment. These institutions and the JRC have developed cooperative programmes now organised in networks. They include utilities, engineering companies, R and D laboratories and Regulatory Bodies. Networks are organised and managed like the successful PISC programme: The Institute for Advanced Materials of JRC plays the role of Operating Agent and Manager of these networks: ENIQ, AMES, NESC, each of them dealing with a specific aspect of fitness for purpose of materials in structural components. There exist strong links between the networks and EC Working Groups on Structural Integrity Codes and Standards. (orig.)

Correct integration of compressors and expanders in above ambient heat exchanger networks

International Nuclear Information System (INIS)

Fu, Chao; Gundersen, Truls

2016-01-01

The Appropriate Placement concept (also referred to as Correct Integration) is fundamental in Pinch Analysis. The placement of reactors, distillation columns, evaporators, heat pumps and heat engines in heat exchanger networks is well established. The placement of pressure changing equipment such as compressors and expanders is complex and less discussed in literature. A major difficulty is that both heat and work (not only heat) are involved. The integration of compressors and expanders separately into heat exchanger networks was recently investigated. A set of theorems were proposed for assisting the design. The problem is even more complex when both compressors and expanders are to be integrated. An important concern is about the sequence of integration with compressors and expanders, i.e. should compressors or expanders be implemented first. This problem is studied and a new theorem is formulated related to the Correct Integration of both compressors and expanders in above ambient heat exchanger networks. The objective is to minimize exergy consumption for the integrated processes. A graphical design methodology is developed for the integration of compressors and expanders into heat exchanger networks above ambient temperature. - Highlights: • The correct integration of compressors and expanders in heat exchanger networks is studied. • A theorem is proposed for heat integration between compressors and expanders. • The total exergy consumption is minimized.

Integration of heterogeneous molecular networks to unravel gene-regulation in Mycobacterium tuberculosis.

Science.gov (United States)

van Dam, Jesse C J; Schaap, Peter J; Martins dos Santos, Vitor A P; Suárez-Diez, María

2014-09-26

Different methods have been developed to infer regulatory networks from heterogeneous omics datasets and to construct co-expression networks. Each algorithm produces different networks and efforts have been devoted to automatically integrate them into consensus sets. However each separate set has an intrinsic value that is diluted and partly lost when building a consensus network. Here we present a methodology to generate co-expression networks and, instead of a consensus network, we propose an integration framework where the different networks are kept and analysed with additional tools to efficiently combine the information extracted from each network. We developed a workflow to efficiently analyse information generated by different inference and prediction methods. Our methodology relies on providing the user the means to simultaneously visualise and analyse the coexisting networks generated by different algorithms, heterogeneous datasets, and a suite of analysis tools. As a show case, we have analysed the gene co-expression networks of Mycobacterium tuberculosis generated using over 600 expression experiments. Regarding DNA damage repair, we identified SigC as a key control element, 12 new targets for LexA, an updated LexA binding motif, and a potential mismatch repair system. We expanded the DevR regulon with 27 genes while identifying 9 targets wrongly assigned to this regulon. We discovered 10 new genes linked to zinc uptake and a new regulatory mechanism for ZuR. The use of co-expression networks to perform system level analysis allows the development of custom made methodologies. As show cases we implemented a pipeline to integrate ChIP-seq data and another method to uncover multiple regulatory layers. Our workflow is based on representing the multiple types of information as network representations and presenting these networks in a synchronous framework that allows their simultaneous visualization while keeping specific associations from the different

Integrated circuit and method of arbitration in a network on an integrated circuit.

NARCIS (Netherlands)

2011-01-01

The invention relates to an integrated circuit and to a method of arbitration in a network on an integrated circuit. According to the invention, a method of arbitration in a network on an integrated circuit is provided, the network comprising a router unit, the router unit comprising a first input

Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.

Science.gov (United States)

Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Olsen, Catharina; Bontempi, Gianluca; Castiglioni, Isabella

2018-01-06

Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

Networks as integrated in research methodologies in PER

DEFF Research Database (Denmark)

Bruun, Jesper

2016-01-01

of using networks to create insightful maps of learning discussions. To conclude, I argue that conceptual blending is a powerful framework for constructing "mixed methods" methodologies that may integrate diverse theories and other methodologies with network methodologies.......In recent years a number of researchers within the PER community have started using network analysis as a new methodology to extend our understanding of teaching and learning physics by viewing these as complex systems. In this paper, I give examples of social, cognitive, and action mapping...... networks and how they can be analyzed. In so doing I show how a network can be methodologically described as a set of relations between a set of entities, and how a network can be characterized and analyzed as a mathematical object. Then, as an illustrative example, I discuss a relatively new example...

Social Network Analysis and Nutritional Behavior: An Integrated Modeling Approach.

Science.gov (United States)

Senior, Alistair M; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J

2016-01-01

Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments.

Building secure network by integrated technology

International Nuclear Information System (INIS)

An Dehai; Xu Rongsheng; Liu Baoxu

2000-01-01

The author introduces a method which can realize the most powerful network security prevention by the network security integrated technologies such as firewall, realtime monitor, network scanner, Web detection and security, etc

Exploratory social network analysis with Pajek. - 2nd ed.

NARCIS (Netherlands)

de Nooy, W.; Mrvar, A.; Batagelj, V.

2011-01-01

This is an extensively revised and expanded second edition of the successful textbook on social network analysis integrating theory, applications, and network analysis using Pajek. The main structural concepts and their applications in social research are introduced with exercises. Pajek software

Integration of 100% Micro-Distributed Energy Resources in the Low Voltage Distribution Network

DEFF Research Database (Denmark)

You, Shi; Segerberg, Helena

2014-01-01

of heat pumps (HPs) and plug-in electric vehicles (PEVs) at 100% penetration level on a representative urban residential low voltage (LV) distribution network of Denmark are investigated by performing a steady-state load flow analysis through an integrated simulation setup. Three DERs integration...... oriented integration strategies, having 100% integration of DER in the provided LV network is feasible.......The existing electricity infrastructure may to a great extent limit a high penetration of the micro-sized Distributed Energy Resources (DERs), due to the physical bottlenecks, e.g. thermal capacitates of cables, transformers and the voltage limitations. In this study, the integration impacts...

Integrative Network Analysis Unveils Convergent Molecular Pathways in Parkinson's Disease and Diabetes

OpenAIRE

Santiago, Jose A.; Potashkin, Judith A.

2013-01-01

Background Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level. ...

Integration of expression data in genome-scale metabolic network reconstructions

Directory of Open Access Journals (Sweden)

Anna S. Blazier

2012-08-01

Full Text Available With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of omics data, quantifying thousands of cellular components across a variety of scales, ranging from mRNA transcript levels to metabolite quantities. Methods are needed to not only integrate this omics data but to also use this data to heighten the predictive capabilities of computational models. Several recent studies have successfully demonstrated how flux balance analysis (FBA, a constraint-based modeling approach, can be used to integrate transcriptomic data into genome-scale metabolic network reconstructions to generate predictive computational models. In this review, we summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.

Requirement analysis and architecture of data communication system for integral reactor

International Nuclear Information System (INIS)

Jeong, K. I.; Kwon, H. J.; Park, J. H.; Park, H. Y.; Koo, I. S.

2005-05-01

When digitalizing the Instrumentation and Control(I and C) systems in Nuclear Power Plants(NPP), a communication network is required for exchanging the digitalized data between I and C equipments in a NPP. A requirements analysis and an analysis of design elements and techniques are required for the design of a communication network. Through the requirements analysis of the code and regulation documents such as NUREG/CR-6082, section 7.9 of NUREG 0800 , IEEE Standard 7-4.3.2 and IEEE Standard 603, the extracted requirements can be used as a design basis and design concept for a detailed design of a communication network in the I and C system of an integral reactor. Design elements and techniques such as a physical topology, protocol transmission media and interconnection device should be considered for designing a communication network. Each design element and technique should be analyzed and evaluated as a portion of the integrated communication network design. In this report, the basic design requirements related to the design of communication network are investigated by using the code and regulation documents and an analysis of the design elements and techniques is performed. Based on these investigation and analysis, the overall architecture including the safety communication network and the non-safety communication network is proposed for an integral reactor

Integrating atomistic molecular dynamics simulations, experiments, and network analysis to study protein dynamics

DEFF Research Database (Denmark)

Papaleo, Elena

2015-01-01

that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome...... with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties...... simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations....

Intelligent sensor networks the integration of sensor networks, signal processing and machine learning

CERN Document Server

Hu, Fei

2012-01-01

Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl

Evaluating airline energy efficiency: An integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure

International Nuclear Information System (INIS)

Xu, Xin; Cui, Qiang

2017-01-01

This paper focuses on evaluating airline energy efficiency, which is firstly divided into four stages: Operations Stage, Fleet Maintenance Stage, Services Stage and Sales Stage. The new four-stage network structure of airline energy efficiency is a modification of existing models. A new approach, integrated with Network Epsilon-based Measure and Network Slacks-based Measure, is applied to assess the overall energy efficiency and divisional efficiency of 19 international airlines from 2008 to 2014. The influencing factors of airline energy efficiency are analyzed through the regression analysis. The results indicate the followings: 1. The integrated model can identify the benchmarking airlines in the overall system and stages. 2. Most airlines' energy efficiencies keep steady during the period, except for some sharply fluctuations. The efficiency decreases mainly centralized in the year 2008–2011, affected by the financial crisis in the USA. 3. The average age of fleet is positively correlated with the overall energy efficiency, and each divisional efficiency has different significant influencing factors. - Highlights: • An integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure is developed. • 19 airlines' energy efficiencies are evaluated. • Garuda Indonesia has the highest overall energy efficiency.

Load balancing in integrated optical wireless networks

DEFF Research Database (Denmark)

Yan, Ying; Dittmann, Lars; Wong, S-W.

2010-01-01

In this paper, we tackle the load balancing problem in Integrated Optical Wireless Networks, where cell breathing technique is used to solve congestion by changing the coverage area of a fully loaded cell tower. Our objective is to design a load balancing mechanism which works closely...... with the integrated control scheme so as to maximize overall network throughput in the integrated network architecture. To the best of our knowledge no load balancing mechanisms, especially based on the Multi-Point Control Protocol (MPCP) defined in the IEEE 802.3ah, have been proposed so far. The major research...... issues are outlined and a cost function based optimization model is developed for power management. In particularly, two alternative feedback schemes are proposed to report wireless network status. Simulation results show that our proposed load balancing mechanism improves network performances....

Structural reliability calculation method based on the dual neural network and direct integration method.

Science.gov (United States)

Li, Haibin; He, Yun; Nie, Xiaobo

2018-01-01

Structural reliability analysis under uncertainty is paid wide attention by engineers and scholars due to reflecting the structural characteristics and the bearing actual situation. The direct integration method, started from the definition of reliability theory, is easy to be understood, but there are still mathematics difficulties in the calculation of multiple integrals. Therefore, a dual neural network method is proposed for calculating multiple integrals in this paper. Dual neural network consists of two neural networks. The neural network A is used to learn the integrand function, and the neural network B is used to simulate the original function. According to the derivative relationships between the network output and the network input, the neural network B is derived from the neural network A. On this basis, the performance function of normalization is employed in the proposed method to overcome the difficulty of multiple integrations and to improve the accuracy for reliability calculations. The comparisons between the proposed method and Monte Carlo simulation method, Hasofer-Lind method, the mean value first-order second moment method have demonstrated that the proposed method is an efficient and accurate reliability method for structural reliability problems.

Combating Forest Corruption: the Forest Integrity Network

NARCIS (Netherlands)

Gupta, A.; Siebert, U.

2004-01-01

This article describes the strategies and activities of the Forest Integrity Network. One of the most important underlying causes of forest degradation is corruption and related illegal logging. The Forest Integrity Network is a timely new initiative to combat forest corruption. Its approach is to

Integrated network analysis reveals potentially novel molecular mechanisms and therapeutic targets of refractory epilepsies.

Directory of Open Access Journals (Sweden)

Hongwei Chu

Full Text Available Epilepsy is a complex neurological disorder and a significant health problem. The pathogenesis of epilepsy remains obscure in a significant number of patients and the current treatment options are not adequate in about a third of individuals which were known as refractory epilepsies (RE. Network medicine provides an effective approach for studying the molecular mechanisms underlying complex diseases. Here we integrated 1876 disease-gene associations of RE and located those genes to human protein-protein interaction (PPI network to obtain 42 significant RE-associated disease modules. The functional analysis of these disease modules showed novel molecular pathological mechanisms of RE, such as the novel enriched pathways (e.g., "presynaptic nicotinic acetylcholine receptors", "signaling by insulin receptor". Further analysis on the relationships between current drug targets and the RE-related disease genes showed the rational mechanisms of most antiepileptic drugs. In addition, we detected ten potential novel drug targets (e.g., KCNA1, KCNA4-6, KCNC3, KCND2, KCNMA1, CAMK2G, CACNB4 and GRM1 located in three RE related disease modules, which might provide novel insights into the new drug discovery for RE therapy.

Energetic and Exergetic Analysis of Low and Medium Temperature District Heating Network Integration

DEFF Research Database (Denmark)

Li, Hongwei; Svendsen, Svend

In this paper, energetic and exergetic approaches were applied to an exemplary low temperature district heating (LTDH) network with supply/return water temperature at 55oC/25 oC. The small LTDH network is annexed to a large medium temperature district heating (MTDH) network. The LTDH network can ...... will reduce the amount of water supply from the MTDH network and improve the system energy conversion efficiency. Through the simulation, the system energetic and exergetic efficiencies based on the two network integration approaches were calculated and evaluated.......In this paper, energetic and exergetic approaches were applied to an exemplary low temperature district heating (LTDH) network with supply/return water temperature at 55oC/25 oC. The small LTDH network is annexed to a large medium temperature district heating (MTDH) network. The LTDH network can...... be supplied through upgrading the return water from the MTDH network with a small centralized heat pump. Alternatively, the supply and return water from the MTDH network can be mixed with a shunt at the junction point to supply the LTDH network. Comparing with the second approach, the heat pump system...

Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics.

Directory of Open Access Journals (Sweden)

István A Kovács

Full Text Available BACKGROUND: Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. METHODOLOGY/PRINCIPAL FINDINGS: Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1 determine persvasively overlapping modules with high resolution; (2 uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3 allow the determination of key network nodes and (4 help to predict network dynamics. CONCLUSIONS/SIGNIFICANCE: The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction.

AN OVERVIEW OF UMTS AND WIMAX NETWORKS INTEGRATION

Directory of Open Access Journals (Sweden)

Dewi Wirastuti

2010-12-01

Full Text Available This paper gives an overview of the network integration of UMTS (Universal Mobile TelecommunicationSystem with WiMAX (Wordwide Interoperability of Microwave Access. A few proposed interworking solutionsand seamless integration of both networks are explained. The best architecture and key procedures that will enablethe integration both networks and handover mechanism for the seamless mobility are presented. Considering thetrend of the current network evolution, which is the convergence between the telecommunications and broadcastworlds, an integration of mobile WiMAX with present 2G, 2.5G or 3G accesses into a homogeneous architecturegoes a long way to achieve the reality of mobile broadband networks. With the advent of mobile WiMAX, a mobilebroadband wireless access solution and based on all-IP (Internet Protocol based OFDMA (Orthogonal FrequencyDivision Multiple Access technology, an UMTS-WiMAX

Integrated control platform for converged optical and wireless networks

DEFF Research Database (Denmark)

Yan, Ying

The next generation of broadband access networks is expected to be heterogeneous. Multiple wired and wireless systems can be integrated, in order to simultaneously provide seamless access with an appropriate Quality of Service (QoS). Wireless networks support ubiquitous connectivity yet low data...... rates, whereas optical networks can offer much higher data rates but only provide fixed connection structures. Their complementary characteristics make the integration of the two networks a promising trend for next generation networks. With combined strengths, the converged network will provide both...... the complementary characteristics of the optical networks and the wireless networks, addresses motivations for their interworking, discusses the current progress in hybrid network architectures as well as the functionalities of a control system, and identifies the achieved research contributions in the integrated...

Structural integration and performance of inter-sectoral public health-related policy networks: An analysis across policy phases.

Science.gov (United States)

Peters, D T J M; Raab, J; Grêaux, K M; Stronks, K; Harting, J

2017-12-01

Inter-sectoral policy networks may be effective in addressing environmental determinants of health with interventions. However, contradictory results are reported on relations between structural network characteristics (i.e., composition and integration) and network performance, such as addressing environmental determinants of health. This study examines these relations in different phases of the policy process. A multiple-case study was performed on four public health-related policy networks. Using a snowball method among network actors, overall and sub-networks per policy phase were identified and the policy sector of each actor was assigned. To operationalise the outcome variable, interventions were classified by the proportion of environmental determinants they addressed. In the overall networks, no relation was found between structural network characteristics and network performance. In most effective cases, the policy development sub-networks were characterised by integration with less interrelations between actors (low cohesion), more equally distributed distances between the actors (low closeness centralisation), and horizontal integration in inter-sectoral cliques. The most effective case had non-public health central actors with less connections in all sub-networks. The results suggest that, to address environmental determinants of health, sub-networks should be inter-sectorally composed in the policy development rather than in the intervention development and implementation phases, and that policy development actors should have the opportunity to connect with other actors, without strong direction from a central actor. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrating Entropy and Closed Frequent Pattern Mining for Social Network Modelling and Analysis

Science.gov (United States)

Adnan, Muhaimenul; Alhajj, Reda; Rokne, Jon

The recent increase in the explicitly available social networks has attracted the attention of the research community to investigate how it would be possible to benefit from such a powerful model in producing effective solutions for problems in other domains where the social network is implicit; we argue that social networks do exist around us but the key issue is how to realize and analyze them. This chapter presents a novel approach for constructing a social network model by an integrated framework that first preparing the data to be analyzed and then applies entropy and frequent closed patterns mining for network construction. For a given problem, we first prepare the data by identifying items and transactions, which arc the basic ingredients for frequent closed patterns mining. Items arc main objects in the problem and a transaction is a set of items that could exist together at one time (e.g., items purchased in one visit to the supermarket). Transactions could be analyzed to discover frequent closed patterns using any of the well-known techniques. Frequent closed patterns have the advantage that they successfully grab the inherent information content of the dataset and is applicable to a broader set of domains. Entropies of the frequent closed patterns arc used to keep the dimensionality of the feature vectors to a reasonable size; it is a kind of feature reduction process. Finally, we analyze the dynamic behavior of the constructed social network. Experiments were conducted on a synthetic dataset and on the Enron corpus email dataset. The results presented in the chapter show that social networks extracted from a feature set as frequent closed patterns successfully carry the community structure information. Moreover, for the Enron email dataset, we present an analysis to dynamically indicate the deviations from each user's individual and community profile. These indications of deviations can be very useful to identify unusual events.

Wellbore Integrity Network

Energy Technology Data Exchange (ETDEWEB)

Carey, James W. [Los Alamos National Laboratory; Bachu, Stefan [Alberta Innovates

2012-06-21

In this presentation, we review the current state of knowledge on wellbore integrity as developed in the IEA Greenhouse Gas Programme's Wellbore Integrity Network. Wells are one of the primary risks to the successful implementation of CO{sub 2} storage programs. Experimental studies show that wellbore materials react with CO{sub 2} (carbonation of cement and corrosion of steel) but the impact on zonal isolation is unclear. Field studies of wells in CO{sub 2}-bearing fields show that CO{sub 2} does migrate external to casing. However, rates and amounts of CO{sub 2} have not been quantified. At the decade time scale, wellbore integrity is driven by construction quality and geomechanical processes. Over longer time-scales (> 100 years), chemical processes (cement degradation and corrosion) become more important, but competing geomechanical processes may preserve wellbore integrity.

Using network analysis to study behavioural phenotypes: an example using domestic dogs.

Science.gov (United States)

Goold, Conor; Vas, Judit; Olsen, Christine; Newberry, Ruth C

2016-10-01

Phenotypic integration describes the complex interrelationships between organismal traits, traditionally focusing on morphology. Recently, research has sought to represent behavioural phenotypes as composed of quasi-independent latent traits. Concurrently, psychologists have opposed latent variable interpretations of human behaviour, proposing instead a network perspective envisaging interrelationships between behaviours as emerging from causal dependencies. Network analysis could also be applied to understand integrated behavioural phenotypes in animals. Here, we assimilate this cross-disciplinary progression of ideas by demonstrating the use of network analysis on survey data collected on behavioural and motivational characteristics of police patrol and detection dogs ( Canis lupus familiaris ). Networks of conditional independence relationships illustrated a number of functional connections between descriptors, which varied between dog types. The most central descriptors denoted desirable characteristics in both patrol and detection dog networks, with 'Playful' being widely correlated and possessing mediating relationships between descriptors. Bootstrap analyses revealed the stability of network results. We discuss the results in relation to previous research on dog personality, and benefits of using network analysis to study behavioural phenotypes. We conclude that a network perspective offers widespread opportunities for advancing the understanding of phenotypic integration in animal behaviour.

Meditation is associated with increased brain network integration.

Science.gov (United States)

van Lutterveld, Remko; van Dellen, Edwin; Pal, Prasanta; Yang, Hua; Stam, Cornelis Jan; Brewer, Judson

2017-09-01

This study aims to identify novel quantitative EEG measures associated with mindfulness meditation. As there is some evidence that meditation is associated with higher integration of brain networks, we focused on EEG measures of network integration. Sixteen novice meditators and sixteen experienced meditators participated in the study. Novice meditators performed a basic meditation practice that supported effortless awareness, which is an important quality of experience related to mindfulness practices, while their EEG was recorded. Experienced meditators performed a self-selected meditation practice that supported effortless awareness. Network integration was analyzed with maximum betweenness centrality and leaf fraction (which both correlate positively with network integration) as well as with diameter and average eccentricity (which both correlate negatively with network integration), based on a phase-lag index (PLI) and minimum spanning tree (MST) approach. Differences between groups were assessed using repeated-measures ANOVA for the theta (4-8 Hz), alpha (8-13 Hz) and lower beta (13-20 Hz) frequency bands. Maximum betweenness centrality was significantly higher in experienced meditators than in novices (P = 0.012) in the alpha band. In the same frequency band, leaf fraction showed a trend toward being significantly higher in experienced meditators than in novices (P = 0.056), while diameter and average eccentricity were significantly lower in experienced meditators than in novices (P = 0.016 and P = 0.028 respectively). No significant differences between groups were observed for the theta and beta frequency bands. These results show that alpha band functional network topology is better integrated in experienced meditators than in novice meditators during meditation. This novel finding provides the rationale to investigate the temporal relation between measures of functional connectivity network integration and meditation quality, for example using

Ties that Bind: A Social Network Approach To Understanding Student Integration and Persistence.

Science.gov (United States)

Thomas, Scott L.

2000-01-01

This study used a social network paradigm to examine college student integration of 329 college freshmen at a private liberal arts college. Analysis of the structural aspects of students' on-campus associations found differential effects of various social network characteristics on student commitment and persistence. (DB)

Structural integration and performance of inter-sectoral public health-related policy networks: An analysis across policy phases

NARCIS (Netherlands)

Peters, D. T. J. M.; Raab, J.; Grêaux, K. M.; Stronks, K.; Harting, J.

2017-01-01

Background: Inter-sectoral policy networks may be effective in addressing environmental determinants of health with interventions. However, contradictory results are reported on relations between structural network characteristics (i.e., composition and integration) and network performance, such as

Structural integration and performance of inter-sectoral public health-related policy networks : An analysis across policy phases

NARCIS (Netherlands)

Peters, Dorothee; Raab, J.; Grêaux, Kimberley M.; Stronks, Karien; Harting, Janneke

2017-01-01

Background: Inter-sectoral policy networks may be effective in addressing environmental determinants of health with interventions. However, contradictory results are reported on relations between structure and network characteristics (i.e., composition and integration) and network performance, such

Integrative Analysis of the Physical Transport Network into Australia.

Directory of Open Access Journals (Sweden)

Robert C Cope

Full Text Available Effective biosecurity is necessary to protect nations and their citizens from a variety of threats, including emerging infectious diseases, agricultural or environmental pests and pathogens, and illegal wildlife trade. The physical pathways by which these threats are transported internationally, predominantly shipping and air traffic, have undergone significant growth and changes in spatial distributions in recent decades. An understanding of the specific pathways and donor-traffic hotspots created by this integrated physical transport network is vital for the development of effective biosecurity strategies into the future. In this study, we analysed the physical transport network into Australia over the period 1999-2012. Seaborne and air traffic were weighted to calculate a "weighted cumulative impact" score for each source region worldwide, each year. High risk source regions, and those source regions that underwent substantial changes in risk over the study period, were determined. An overall risk ranking was calculated by integrating across all possible weighting combinations. The source regions having greatest overall physical connectedness with Australia were Singapore, which is a global transport hub, and the North Island of New Zealand, a close regional trading partner with Australia. Both those regions with large amounts of traffic across multiple vectors (e.g., Hong Kong, and those with high levels of traffic of only one type (e.g., Bali, Indonesia with respect to passenger flights, were represented among high risk source regions. These data provide a baseline model for the transport of individuals and commodities against which the effectiveness of biosecurity controls may be assessed, and are a valuable tool in the development of future biosecurity policy.

Integrated network design and scheduling problems :

Energy Technology Data Exchange (ETDEWEB)

Nurre, Sarah G.; Carlson, Jeffrey J.

2014-01-01

We consider the class of integrated network design and scheduling problems. These problems focus on selecting and scheduling operations that will change the characteristics of a network, while being speci cally concerned with the performance of the network over time. Motivating applications of INDS problems include infrastructure restoration after extreme events and building humanitarian distribution supply chains. While similar models have been proposed, no one has performed an extensive review of INDS problems from their complexity, network and scheduling characteristics, information, and solution methods. We examine INDS problems under a parallel identical machine scheduling environment where the performance of the network is evaluated by solving classic network optimization problems. We classify that all considered INDS problems as NP-Hard and propose a novel heuristic dispatching rule algorithm that selects and schedules sets of arcs based on their interactions in the network. We present computational analysis based on realistic data sets representing the infrastructures of coastal New Hanover County, North Carolina, lower Manhattan, New York, and a realistic arti cial community CLARC County. These tests demonstrate the importance of a dispatching rule to arrive at near-optimal solutions during real-time decision making activities. We extend INDS problems to incorporate release dates which represent the earliest an operation can be performed and exible release dates through the introduction of specialized machine(s) that can perform work to move the release date earlier in time. An online optimization setting is explored where the release date of a component is not known.

Dynamic stability analysis of fractional order leaky integrator echo state neural networks

Science.gov (United States)

Pahnehkolaei, Seyed Mehdi Abedi; Alfi, Alireza; Tenreiro Machado, J. A.

2017-06-01

The Leaky integrator echo state neural network (Leaky-ESN) is an improved model of the recurrent neural network (RNN) and adopts an interconnected recurrent grid of processing neurons. This paper presents a new proof for the convergence of a Lyapunov candidate function to zero when time tends to infinity by means of the Caputo fractional derivative with order lying in the range (0, 1). The stability of Fractional-Order Leaky-ESN (FO Leaky-ESN) is then analyzed, and the existence, uniqueness and stability of the equilibrium point are provided. A numerical example demonstrates the feasibility of the proposed method.

Integrated situational awareness for cyber attack detection, analysis, and mitigation

Science.gov (United States)

Cheng, Yi; Sagduyu, Yalin; Deng, Julia; Li, Jason; Liu, Peng

2012-06-01

Real-time cyberspace situational awareness is critical for securing and protecting today's enterprise networks from various cyber threats. When a security incident occurs, network administrators and security analysts need to know what exactly has happened in the network, why it happened, and what actions or countermeasures should be taken to quickly mitigate the potential impacts. In this paper, we propose an integrated cyberspace situational awareness system for efficient cyber attack detection, analysis and mitigation in large-scale enterprise networks. Essentially, a cyberspace common operational picture will be developed, which is a multi-layer graphical model and can efficiently capture and represent the statuses, relationships, and interdependencies of various entities and elements within and among different levels of a network. Once shared among authorized users, this cyberspace common operational picture can provide an integrated view of the logical, physical, and cyber domains, and a unique visualization of disparate data sets to support decision makers. In addition, advanced analyses, such as Bayesian Network analysis, will be explored to address the information uncertainty, dynamic and complex cyber attack detection, and optimal impact mitigation issues. All the developed technologies will be further integrated into an automatic software toolkit to achieve near real-time cyberspace situational awareness and impact mitigation in large-scale computer networks.

Students' network integration vs. persistence in introductory physics courses

Science.gov (United States)

Zwolak, Justyna; Brewe, Eric

2017-01-01

Society is constantly in flux, which demands the continuous development of our educational system to meet new challenges and impart the appropriate knowledge/skills to students. In order to improve student learning, among other things, the way we are teaching has significantly changed over the past few decades. We are moving away from traditional, lecture-based teaching towards more interactive, engagement-based strategies. A current, major challenge for universities is to increase student retention. While students' academic and social integration into an institution seems to be vital for student retention, research on the effect of interpersonal interactions is rare. I use of network analysis to investigate academic and social experiences of students in and beyond the classroom. In particular, there is a compelling case that transformed physics classes, such as Modeling Instruction (MI), promote persistence by the creation of learning communities that support the integration of students into the university. I will discuss recent results on pattern development in networks of MI students' interactions throughout the semester, as well as the effect of students' position within the network on their persistence in physics.

Magnets and Seekers: A Network Perspective on Academic Integration inside Two Residential Communities

Science.gov (United States)

Smith, Rachel A.

2015-01-01

Residential learning communities aim to foster increased academic and social integration, ideally leading to greater student success. However, the concept of academic integration is often conceptualized and measured at the individual level, rather than the theoretically more consistent community level. Network analysis provides a paradigm and…

Integrated Optoelectronic Networks for Application-Driven Multicore Computing

Science.gov (United States)

2017-05-08

AFRL-AFOSR-VA-TR-2017-0102 Integrated Optoelectronic Networks for Application- Driven Multicore Computing Sudeep Pasricha COLORADO STATE UNIVERSITY...AND SUBTITLE Integrated Optoelectronic Networks for Application-Driven Multicore Computing 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA9550-13-1-0110 5c...and supportive materials with innovative architectural designs that integrate these components according to system-wide application needs. 15

Integration of a network aware traffic generation device into a computer network emulation platform

CSIR Research Space (South Africa)

Von Solms, S

2014-07-01

Full Text Available Flexible, open source network emulation tools can provide network researchers with significant benefits regarding network behaviour and performance. The evaluation of these networks can benefit greatly from the integration of realistic, network...

European networks in industrial integrity

International Nuclear Information System (INIS)

Crutzen, S.

1995-01-01

Several institutions and electrical utilities in Europe, including the Joint Research Centre (JRC), have the capability to deal with several of the problems posed by the operation and aging of structural components and with their structural integrity assessment. These institutions and the JRC have developed cooperative programmes and organized themselves into networks. This article describes the structure and objective of the existing networks. 3 figs

MINET [momentum integral network] code documentation

International Nuclear Information System (INIS)

Van Tuyle, G.J.; Nepsee, T.C.; Guppy, J.G.

1989-12-01

The MINET computer code, developed for the transient analysis of fluid flow and heat transfer, is documented in this four-part reference. In Part 1, the MINET models, which are based on a momentum integral network method, are described. The various aspects of utilizing the MINET code are discussed in Part 2, The User's Manual. The third part is a code description, detailing the basic code structure and the various subroutines and functions that make up MINET. In Part 4, example input decks, as well as recent validation studies and applications of MINET are summarized. 32 refs., 36 figs., 47 tabs

Integrating Social Networks in Teaching in Higher Education

Science.gov (United States)

Abousoliman, Onsy

2017-01-01

In response to the emerging and swiftly developing digital tools, this dissertation investigated integrating a specific category of these tools, social networks, in teaching in higher education. The study focused on exploring how social networks integration might impact the teaching/learning process and on investigating the challenges that could…

Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses.

Science.gov (United States)

Luo, Jie; Xu, Pei; Cao, Peijian; Wan, Hongjian; Lv, Xiaonan; Xu, Shengchun; Wang, Gangjun; Cook, Melloni N; Jones, Byron C; Lu, Lu; Wang, Xusheng

2018-01-01

Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE) but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1), down-regulation in NOE but rescue in RSE (pattern 2), up-regulation in both restraint stress followed by a saline injection (RSS) and NOE, and further amplification in RSE (pattern 3), and up-regulation in RSS but reduction in both NOE and RSE (pattern 4). We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs) to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA) signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.

Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses

Directory of Open Access Journals (Sweden)

Jie Luo

2018-04-01

Full Text Available Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1, down-regulation in NOE but rescue in RSE (pattern 2, up-regulation in both restraint stress followed by a saline injection (RSS and NOE, and further amplification in RSE (pattern 3, and up-regulation in RSS but reduction in both NOE and RSE (pattern 4. We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.

Reconstruction of biological networks based on life science data integration.

Science.gov (United States)

Kormeier, Benjamin; Hippe, Klaus; Arrigo, Patrizio; Töpel, Thoralf; Janowski, Sebastian; Hofestädt, Ralf

2010-10-27

For the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. Therefore, based on relevant molecular database and information systems, biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the applications BioDWH--an integration toolkit for building life science data warehouses, CardioVINEdb--a information system for biological data in cardiovascular-disease and VANESA--a network editor for modeling and simulation of biological networks. Based on this integration process, the system supports the generation of biological network models. A case study of a cardiovascular-disease related gene-regulated biological network is also presented.

Analysis of network motifs in cellular regulation: Structural similarities, input-output relations and signal integration.

Science.gov (United States)

Straube, Ronny

2017-12-01

Much of the complexity of regulatory networks derives from the necessity to integrate multiple signals and to avoid malfunction due to cross-talk or harmful perturbations. Hence, one may expect that the input-output behavior of larger networks is not necessarily more complex than that of smaller network motifs which suggests that both can, under certain conditions, be described by similar equations. In this review, we illustrate this approach by discussing the similarities that exist in the steady state descriptions of a simple bimolecular reaction, covalent modification cycles and bacterial two-component systems. Interestingly, in all three systems fundamental input-output characteristics such as thresholds, ultrasensitivity or concentration robustness are described by structurally similar equations. Depending on the system the meaning of the parameters can differ ranging from protein concentrations and affinity constants to complex parameter combinations which allows for a quantitative understanding of signal integration in these systems. We argue that this approach may also be extended to larger regulatory networks. Copyright © 2017 Elsevier B.V. All rights reserved.

Network Analysis of Rodent Transcriptomes in Spaceflight

Science.gov (United States)

Ramachandran, Maya; Fogle, Homer; Costes, Sylvain

2017-01-01

Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

Ontology-based Vaccine and Drug Adverse Event Representation and Theory-guided Systematic Causal Network Analysis toward Integrative Pharmacovigilance Research.

Science.gov (United States)

He, Yongqun

2016-06-01

Compared with controlled terminologies ( e.g. , MedDRA, CTCAE, and WHO-ART), the community-based Ontology of AEs (OAE) has many advantages in adverse event (AE) classifications. The OAE-derived Ontology of Vaccine AEs (OVAE) and Ontology of Drug Neuropathy AEs (ODNAE) serve as AE knowledge bases and support data integration and analysis. The Immune Response Gene Network Theory explains molecular mechanisms of vaccine-related AEs. The OneNet Theory of Life treats the whole process of a life of an organism as a single complex and dynamic network ( i.e. , OneNet). A new "OneNet effectiveness" tenet is proposed here to expand the OneNet theory. Derived from the OneNet theory, the author hypothesizes that one human uses one single genotype-rooted mechanism to respond to different vaccinations and drug treatments, and experimentally identified mechanisms are manifestations of the OneNet blueprint mechanism under specific conditions. The theories and ontologies interact together as semantic frameworks to support integrative pharmacovigilance research.

NIF ICCS network design and loading analysis

International Nuclear Information System (INIS)

Tietbohl, G; Bryant, R

1998-01-01

The National Ignition Facility (NIF) is housed within a large facility about the size of two football fields. The Integrated Computer Control System (ICCS) is distributed throughout this facility and requires the integration of about 40,000 control points and over 500 video sources. This integration is provided by approximately 700 control computers distributed throughout the NIF facility and a network that provides the communication infrastructure. A main control room houses a set of seven computer consoles providing operator access and control of the various distributed front-end processors (FEPs). There are also remote workstations distributed within the facility that allow provide operator console functions while personnel are testing and troubleshooting throughout the facility. The operator workstations communicate with the FEPs which implement the localized control and monitoring functions. There are different types of FEPs for the various subsystems being controlled. This report describes the design of the NIF ICCS network and how it meets the traffic loads that will are expected and the requirements of the Sub-System Design Requirements (SSDR's). This document supersedes the earlier reports entitled Analysis of the National Ignition Facility Network, dated November 6, 1996 and The National Ignition Facility Digital Video and Control Network, dated July 9, 1996. For an overview of the ICCS, refer to the document NIF Integrated Computer Controls System Description (NIF-3738)

Reconstruction of biological networks based on life science data integration

Directory of Open Access Journals (Sweden)

Kormeier Benjamin

2010-06-01

Full Text Available For the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. Therefore, based on relevant molecular database and information systems, biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the applications BioDWH - an integration toolkit for building life science data warehouses, CardioVINEdb - a information system for biological data in cardiovascular-disease and VANESA- a network editor for modeling and simulation of biological networks. Based on this integration process, the system supports the generation of biological network models. A case study of a cardiovascular-disease related gene-regulated biological network is also presented.

The integration of weighted human gene association networks based on link prediction.

Science.gov (United States)

Yang, Jian; Yang, Tinghong; Wu, Duzhi; Lin, Limei; Yang, Fan; Zhao, Jing

2017-01-31

Physical and functional interplays between genes or proteins have important biological meaning for cellular functions. Some efforts have been made to construct weighted gene association meta-networks by integrating multiple biological resources, where the weight indicates the confidence of the interaction. However, it is found that these existing human gene association networks share only quite limited overlapped interactions, suggesting their incompleteness and noise. Here we proposed a workflow to construct a weighted human gene association network using information of six existing networks, including two weighted specific PPI networks and four gene association meta-networks. We applied link prediction algorithm to predict possible missing links of the networks, cross-validation approach to refine each network and finally integrated the refined networks to get the final integrated network. The common information among the refined networks increases notably, suggesting their higher reliability. Our final integrated network owns much more links than most of the original networks, meanwhile its links still keep high functional relevance. Being used as background network in a case study of disease gene prediction, the final integrated network presents good performance, implying its reliability and application significance. Our workflow could be insightful for integrating and refining existing gene association data.

Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks

Directory of Open Access Journals (Sweden)

Raja Jurdak

2008-11-01

Full Text Available Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper.

Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks.

Science.gov (United States)

Jurdak, Raja; Nafaa, Abdelhamid; Barbirato, Alessio

2008-11-24

Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper.

Integrating Network Awareness in ATLAS Distributed Computing Using the ANSE Project

CERN Document Server

Klimentov, Alexei; The ATLAS collaboration; Petrosyan, Artem; Batista, Jorge Horacio; Mc Kee, Shawn Patrick

2015-01-01

A crucial contributor to the success of the massively scaled global computing system that delivers the analysis needs of the LHC experiments is the networking infrastructure upon which the system is built. The experiments have been able to exploit excellent high-bandwidth networking in adapting their computing models for the most efficient utilization of resources. New advanced networking technologies now becoming available such as software defined networking hold the potential of further leveraging the network to optimize workflows and dataflows, through proactive control of the network fabric on the part of high level applications such as experiment workload management and data management systems. End to end monitoring of networks using perfSONAR combined with data flow performance metrics further allows applications to adapt based on real time conditions. We will describe efforts underway in ATLAS on integrating network awareness at the application level, particularly in workload management, building upon ...

Industrial entrepreneurial network: Structural and functional analysis

Science.gov (United States)

Medvedeva, M. A.; Davletbaev, R. H.; Berg, D. B.; Nazarova, J. J.; Parusheva, S. S.

2016-12-01

Structure and functioning of two model industrial entrepreneurial networks are investigated in the present paper. One of these networks is forming when implementing an integrated project and consists of eight agents, which interact with each other and external environment. The other one is obtained from the municipal economy and is based on the set of the 12 real business entities. Analysis of the networks is carried out on the basis of the matrix of mutual payments aggregated over the certain time period. The matrix is created by the methods of experimental economics. Social Network Analysis (SNA) methods and instruments were used in the present research. The set of basic structural characteristics was investigated: set of quantitative parameters such as density, diameter, clustering coefficient, different kinds of centrality, and etc. They were compared with the random Bernoulli graphs of the corresponding size and density. Discovered variations of random and entrepreneurial networks structure are explained by the peculiarities of agents functioning in production network. Separately, were identified the closed exchange circuits (cyclically closed contours of graph) forming an autopoietic (self-replicating) network pattern. The purpose of the functional analysis was to identify the contribution of the autopoietic network pattern in its gross product. It was found that the magnitude of this contribution is more than 20%. Such value allows using of the complementary currency in order to stimulate economic activity of network agents.

Validation of network communicability metrics for the analysis of brain structural networks.

Directory of Open Access Journals (Sweden)

Jennifer Andreotti

Full Text Available Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

NET-2 Network Analysis Program

International Nuclear Information System (INIS)

Malmberg, A.F.

1974-01-01

The NET-2 Network Analysis Program is a general purpose digital computer program which solves the nonlinear time domain response and the linearized small signal frequency domain response of an arbitrary network of interconnected components. NET-2 is capable of handling a variety of components and has been applied to problems in several engineering fields, including electronic circuit design and analysis, missile flight simulation, control systems, heat flow, fluid flow, mechanical systems, structural dynamics, digital logic, communications network design, solid state device physics, fluidic systems, and nuclear vulnerability due to blast, thermal, gamma radiation, neutron damage, and EMP effects. Network components may be selected from a repertoire of built-in models or they may be constructed by the user through appropriate combinations of mathematical, empirical, and topological functions. Higher-level components may be defined by subnetworks composed of any combination of user-defined components and built-in models. The program provides a modeling capability to represent and intermix system components on many levels, e.g., from hole and electron spatial charge distributions in solid state devices through discrete and integrated electronic components to functional system blocks. NET-2 is capable of simultaneous computation in both the time and frequency domain, and has statistical and optimization capability. Network topology may be controlled as a function of the network solution. (U.S.)

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.

Trends in Integrated Ship Control Networking

DEFF Research Database (Denmark)

Jørgensen, N.; Nielsen, Jens Frederik Dalsgaard

1997-01-01

Integrated Ship Control systems can be designed as robust, distributed, autonomous control systems. The EU funded ATOMOS and ATOMOS II projects involves both technical and non technical aspects of this process. A reference modelling concept giving an outline of a generic ISC system covering...... the network and the equipment connected to it, a framework for verification of network functionality and performance by simulation and a general distribution platform for ISC systems, The ATOMOS Network, are results of this work....

An Integrated Solution for Performing Thermo-fluid Conjugate Analysis

Science.gov (United States)

Kornberg, Oren

2009-01-01

A method has been developed which integrates a fluid flow analyzer and a thermal analyzer to produce both steady state and transient results of 1-D, 2-D, and 3-D analysis models. The Generalized Fluid System Simulation Program (GFSSP) is a one dimensional, general purpose fluid analysis code which computes pressures and flow distributions in complex fluid networks. The MSC Systems Improved Numerical Differencing Analyzer (MSC.SINDA) is a one dimensional general purpose thermal analyzer that solves network representations of thermal systems. Both GFSSP and MSC.SINDA have graphical user interfaces which are used to build the respective model and prepare it for analysis. The SINDA/GFSSP Conjugate Integrator (SGCI) is a formbase graphical integration program used to set input parameters for the conjugate analyses and run the models. The contents of this paper describes SGCI and its thermo-fluids conjugate analysis techniques and capabilities by presenting results from some example models including the cryogenic chill down of a copper pipe, a bar between two walls in a fluid stream, and a solid plate creating a phase change in a flowing fluid.

An integrated approach to uncover quality marker underlying the effects of Alisma orientale on lipid metabolism, using chemical analysis and network pharmacology.

Science.gov (United States)

Liao, Maoliang; Shang, Haihua; Li, Yazhuo; Li, Tian; Wang, Miao; Zheng, Yanan; Hou, Wenbin; Liu, Changxiao

2018-06-01

Quality control of traditional Chinese medicines is currently a great concern, due to the correlation between the quality control indicators and clinic effect is often questionable. According to the "multi-components and multi-targets" property of TCMs, a new special quality and bioactivity evaluation system is urgently needed. Present study adopted an integrated approach to provide new insights relating to uncover quality marker underlying the effects of Alisma orientale (AO) on lipid metabolism. In this paper, guided by the concept of the quality marker (Q-marker), an integrated strategies "effect-compound-target-fingerprint" was established to discovery and screen the potential quality marker of AO based on network pharmacology and chemical analysis. Firstly, a bioactivity evaluation was performed to screen the main active fractions. Then the chemical compositions were rapidly identified by chemical analysis. Next, networks were constructed to illuminate the interactions between these component and their targets for lipid metabolism, and the potential Q-marker of AO was initially screened. Finally, the activity of the Q-markers was validated in vitro. 50% ethanol extract fraction was found to have the strongest lipid-lowering activity. Then, the network pharmacology was used to clarify the unique relationship between the Q-markers and their integral pharmacological action. Combined with the results obtained, five active ingredients in the 50% ethanol extract fraction were given special considerations to be representative Q-markers: Alisol A, Alisol B, Alisol A 23-acetate, Alisol B 23-acetate and Alisol A 24-acetate, respectively. The chromatographic fingerprints based Q-marker was establishment. The integrated Q-marker screen may offer an alternative quality assessment of herbal medicines. Copyright © 2018. Published by Elsevier GmbH.

Romanian network for structural integrity assessment of nuclear components

International Nuclear Information System (INIS)

Roth, Maria; Constantinescu, Dan Mihai; Brad, Sebastian; Ducu, Catalin

2008-01-01

Full text: Based of the Romanian option to develop and operate nuclear facilities, using as model the networks created at European level and taking into account the international importance of the structural integrity assessments for lifetime extension of the nuclear components, a national Project started since 2005 in the framework of the National Program 'Research of Excellence', Modulus I 2006-2008, managed by the Ministry of Education and Research. Entitled 'Integrated Network for Structural Integrity Monitoring of Critical Components in Nuclear Facilities', with the acronym RIMIS, the Project had two main objectives: - to elaborate a procedure applicable to the structural integrity assessment of the critical components used in Romanian nuclear facilities; - to integrate the national networking in a similar one, at European level, to enhance the scientific significance of Romanian R and D organizations as well as to increase the contribution to solving one of the major issue of the nuclear field. The paper aimed to present the activities performed in the Romanian institutes, involved in the Project, the final results obtained as part of the R and D activities, including experimental, theoretical and modeling ones regarding structural integrity assessment of nuclear components employed in CANDU type reactors. Also the activity carried out in the framework of the NULIFE network, created at European level of the FP6 Program and sustained by the RIMIS network will be described. (authors)

Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks

Directory of Open Access Journals (Sweden)

Alina Sîrbu

2015-05-01

Full Text Available Microarray technologies have been the basis of numerous important findings regarding gene expression in the few last decades. Studies have generated large amounts of data describing various processes, which, due to the existence of public databases, are widely available for further analysis. Given their lower cost and higher maturity compared to newer sequencing technologies, these data continue to be produced, even though data quality has been the subject of some debate. However, given the large volume of data generated, integration can help overcome some issues related, e.g., to noise or reduced time resolution, while providing additional insight on features not directly addressed by sequencing methods. Here, we present an integration test case based on public Drosophila melanogaster datasets (gene expression, binding site affinities, known interactions. Using an evolutionary computation framework, we show how integration can enhance the ability to recover transcriptional gene regulatory networks from these data, as well as indicating which data types are more important for quantitative and qualitative network inference. Our results show a clear improvement in performance when multiple datasets are integrated, indicating that microarray data will remain a valuable and viable resource for some time to come.

Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks.

Science.gov (United States)

Sîrbu, Alina; Crane, Martin; Ruskin, Heather J

2015-05-14

Microarray technologies have been the basis of numerous important findings regarding gene expression in the few last decades. Studies have generated large amounts of data describing various processes, which, due to the existence of public databases, are widely available for further analysis. Given their lower cost and higher maturity compared to newer sequencing technologies, these data continue to be produced, even though data quality has been the subject of some debate. However, given the large volume of data generated, integration can help overcome some issues related, e.g., to noise or reduced time resolution, while providing additional insight on features not directly addressed by sequencing methods. Here, we present an integration test case based on public Drosophila melanogaster datasets (gene expression, binding site affinities, known interactions). Using an evolutionary computation framework, we show how integration can enhance the ability to recover transcriptional gene regulatory networks from these data, as well as indicating which data types are more important for quantitative and qualitative network inference. Our results show a clear improvement in performance when multiple datasets are integrated, indicating that microarray data will remain a valuable and viable resource for some time to come.

Integrated topology optimisation of multi-energy networks

NARCIS (Netherlands)

Mazairac, L.A.J.; Salenbien, R.; Vanhoudt, D.; Desmedt, J.; Vries, de B.

2015-01-01

Multi-carrier hybrid energy distribution net- works provide flexibility in case of network malfunctions, energy shortages and price fluctuations through energy conversion and storage. Therefore hybrid networks can cope with large-scale integration of distributed and intermittent renewable energy

Atypical language laterality is associated with large-scale disruption of network integration in children with intractable focal epilepsy.

Science.gov (United States)

Ibrahim, George M; Morgan, Benjamin R; Doesburg, Sam M; Taylor, Margot J; Pang, Elizabeth W; Donner, Elizabeth; Go, Cristina Y; Rutka, James T; Snead, O Carter

2015-04-01

Epilepsy is associated with disruption of integration in distributed networks, together with altered localization for functions such as expressive language. The relation between atypical network connectivity and altered localization is unknown. In the current study we tested whether atypical expressive language laterality was associated with the alteration of large-scale network integration in children with medically-intractable localization-related epilepsy (LRE). Twenty-three right-handed children (age range 8-17) with medically-intractable LRE performed a verb generation task in fMRI. Language network activation was identified and the Laterality index (LI) was calculated within the pars triangularis and pars opercularis. Resting-state data from the same cohort were subjected to independent component analysis. Dual regression was used to identify associations between resting-state integration and LI values. Higher positive values of the LI, indicating typical language localization were associated with stronger functional integration of various networks including the default mode network (DMN). The normally symmetric resting-state networks showed a pattern of lateralized connectivity mirroring that of language function. The association between atypical language localization and network integration implies a widespread disruption of neural network development. These findings may inform the interpretation of localization studies by providing novel insights into reorganization of neural networks in epilepsy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling and Simulation of Handover Scheme in Integrated EPON-WiMAX Networks

DEFF Research Database (Denmark)

Yan, Ying; Dittmann, Lars

2011-01-01

In this paper, we tackle the seamless handover problem in integrated optical wireless networks. Our model applies for the convergence network of EPON and WiMAX and a mobilityaware signaling protocol is proposed. The proposed handover scheme, Integrated Mobility Management Scheme (IMMS), is assisted...... by enhancing the traditional MPCP signaling protocol, which cooperatively collects mobility information from the front-end wireless network and makes centralized bandwidth allocation decisions in the backhaul optical network. The integrated network architecture and the joint handover scheme are simulated using...... OPNET modeler. Results show validation of the protocol, i.e., integrated handover scheme gains better network performances....

Integration of gene expression and methylation to unravel biological networks in glioblastoma patients.

Science.gov (United States)

Gadaleta, Francesco; Bessonov, Kyrylo; Van Steen, Kristel

2017-02-01

The vast amount of heterogeneous omics data, encompassing a broad range of biomolecular information, requires novel methods of analysis, including those that integrate the available levels of information. In this work, we describe Regression2Net, a computational approach that is able to integrate gene expression and genomic or methylation data in two steps. First, penalized regressions are used to build Expression-Expression (EEnet) and Expression-Genomic or Expression-Methylation (EMnet) networks. Second, network theory is used to highlight important communities of genes. When applying our approach, Regression2Net to gene expression and methylation profiles for individuals with glioblastoma multiforme, we identified, respectively, 284 and 447 potentially interesting genes in relation to glioblastoma pathology. These genes showed at least one connection in the integrated networks ANDnet and XORnet derived from aforementioned EEnet and EMnet networks. Although the edges in ANDnet occur in both EEnet and EMnet, the edges in XORnet occur in EMnet but not in EEnet. In-depth biological analysis of connected genes in ANDnet and XORnet revealed genes that are related to energy metabolism, cell cycle control (AATF), immune system response, and several cancer types. Importantly, we observed significant overrepresentation of cancer-related pathways including glioma, especially in the XORnet network, suggesting a nonignorable role of methylation in glioblastoma multiforma. In the ANDnet, we furthermore identified potential glioma suppressor genes ACCN3 and ACCN4 linked to the NBPF1 neuroblastoma breakpoint family, as well as numerous ABC transporter genes (ABCA1, ABCB1) suggesting drug resistance of glioblastoma tumors. © 2016 WILEY PERIODICALS, INC.

Integrating Data and Networks: Human Factors

Science.gov (United States)

Chen, R. S.

2012-12-01

The development of technical linkages and interoperability between scientific networks is a necessary but not sufficient step towards integrated use and application of networked data and information for scientific and societal benefit. A range of "human factors" must also be addressed to ensure the long-term integration, sustainability, and utility of both the interoperable networks themselves and the scientific data and information to which they provide access. These human factors encompass the behavior of both individual humans and human institutions, and include system governance, a common framework for intellectual property rights and data sharing, consensus on terminology, metadata, and quality control processes, agreement on key system metrics and milestones, the compatibility of "business models" in the short and long term, harmonization of incentives for cooperation, and minimization of disincentives. Experience with several national and international initiatives and research programs such as the International Polar Year, the Group on Earth Observations, the NASA Earth Observing Data and Information System, the U.S. National Spatial Data Infrastructure, the Global Earthquake Model, and the United Nations Spatial Data Infrastructure provide a range of lessons regarding these human factors. Ongoing changes in science, technology, institutions, relationships, and even culture are creating both opportunities and challenges for expanded interoperability of scientific networks and significant improvement in data integration to advance science and the use of scientific data and information to achieve benefits for society as a whole.

An Integrative Analysis of Preeclampsia Based on the Construction of an Extended Composite Network Featuring Protein-Protein Physical Interactions and Transcriptional Relationships.

Directory of Open Access Journals (Sweden)

Daniel Vaiman

Full Text Available Preeclampsia (PE is a pregnancy disorder defined by hypertension and proteinuria. This disease remains a major cause of maternal and fetal morbidity and mortality. Defective placentation is generally described as being at the root of the disease. The characterization of the transcriptome signature of the preeclamptic placenta has allowed to identify differentially expressed genes (DEGs. However, we still lack a detailed knowledge on how these DEGs impact the function of the placenta. The tools of network biology offer a methodology to explore complex diseases at a systems level. In this study we performed a cross-platform meta-analysis of seven publically available gene expression datasets comparing non-pathological and preeclamptic placentas. Using the rank product algorithm we identified a total of 369 DEGs consistently modified in PE. The DEGs were used as seeds to build both an extended physical protein-protein interactions network and a transcription factors regulatory network. Topological and clustering analysis was conducted to analyze the connectivity properties of the networks. Finally both networks were merged into a composite network which presents an integrated view of the regulatory pathways involved in preeclampsia and the crosstalk between them. This network is a useful tool to explore the relationship between the DEGs and enable hypothesis generation for functional experimentation.

Towards Integrated Marmara Strong Motion Network

Science.gov (United States)

Durukal, E.; Erdik, M.; Safak, E.; Ansal, A.; Ozel, O.; Alcik, H.; Mert, A.; Kafadar, N.; Korkmaz, A.; Kurtulus, A.

2009-04-01

Array (72 ch. dense accelerometric array to be installed in 2010) - Gemlik Array (a dense basin array of 8 stations, to be installed in 2010) The objectives of these systems and networks are: (1) to produce rapid earthquake intensity, damage and loss assessment information after an earthquake (in the case of IERREWS), (2) to monitor conditions of structural systems, (3) to develop real-time data processing, analysis, and damage detection and location tools (in the case of structural networks) after an extreme event, (4) to assess spatial properties of strong ground motion and ground strain, and to characterise basin response (in the case of special arrays), (5) to investigate site response and wave propagation (in the case of vertical array). Ground motion data obtained from these strong motion networks have and are being used for investigations of attenuation, spatial variation (coherence), simulation benchmarking, source modeling, site response, seismic microzonation, system identification and structural model verification and structural health control. In addition to the systems and networks outlined above there are two temporary networks: KIMNET - a dense urban noise and microtremor network consisting of 50 broadband stations expected to be operational in mid 2009, and SOSEWIN - a 20-station, self-organizing structural integrated array at Ataköy in Istanbul.

Probabilistic Steady-State Operation and Interaction Analysis of Integrated Electricity, Gas and Heating Systems

Directory of Open Access Journals (Sweden)

Lun Yang

2018-04-01

Full Text Available The existing studies on probabilistic steady-state analysis of integrated energy systems (IES are limited to integrated electricity and gas networks or integrated electricity and heating networks. This paper proposes a probabilistic steady-state analysis of integrated electricity, gas and heating networks (EGH-IES. Four typical operation modes of an EGH-IES are presented at first. The probabilistic energy flow problem of the EGS-IES considering its operation modes and correlated uncertainties in wind/solar power and electricity/gas/heat loads is then formulated and solved by the Monte Carlo method based on Latin hypercube sampling and Nataf transformation. Numerical simulations are conducted on a sample EGH-IES working in the “electricity/gas following heat” mode to verify the probabilistic analysis proposed in this paper and to study the effects of uncertainties and correlations on the operation of the EGH-IES, especially uncertainty transmissions among the subnetworks.

Definition, analysis and development of an optical data distribution network for integrated avionics and control systems. Part 2: Component development and system integration

Science.gov (United States)

Yen, H. W.; Morrison, R. J.

1984-01-01

Fiber optic transmission is emerging as an attractive concept in data distribution onboard civil aircraft. Development of an Optical Data Distribution Network for Integrated Avionics and Control Systems for commercial aircraft will provide a data distribution network that gives freedom from EMI-RFI and ground loop problems, eliminates crosstalk and short circuits, provides protection and immunity from lightning induced transients and give a large bandwidth data transmission capability. In addition there is a potential for significantly reducing the weight and increasing the reliability over conventional data distribution networks. Wavelength Division Multiplexing (WDM) is a candidate method for data communication between the various avionic subsystems. With WDM all systems could conceptually communicate with each other without time sharing and requiring complicated coding schemes for each computer and subsystem to recognize a message. However, the state of the art of optical technology limits the application of fiber optics in advanced integrated avionics and control systems. Therefore, it is necessary to address the architecture for a fiber optics data distribution system for integrated avionics and control systems as well as develop prototype components and systems.

Perioperative and ICU Healthcare Analytics within a Veterans Integrated System Network: a Qualitative Gap Analysis.

Science.gov (United States)

Mudumbai, Seshadri; Ayer, Ferenc; Stefanko, Jerry

2017-08-01

Health care facilities are implementing analytics platforms as a way to document quality of care. However, few gap analyses exist on platforms specifically designed for patients treated in the Operating Room, Post-Anesthesia Care Unit, and Intensive Care Unit (ICU). As part of a quality improvement effort, we undertook a gap analysis of an existing analytics platform within the Veterans Healthcare Administration. The objectives were to identify themes associated with 1) current clinical use cases and stakeholder needs; 2) information flow and pain points; and 3) recommendations for future analytics development. Methods consisted of semi-structured interviews in 2 phases with a diverse set (n = 9) of support personnel and end users from five facilities across a Veterans Integrated Service Network. Phase 1 identified underlying needs and previous experiences with the analytics platform across various roles and operational responsibilities. Phase 2 validated preliminary feedback, lessons learned, and recommendations for improvement. Emerging themes suggested that the existing system met a small pool of national reporting requirements. However, pain points were identified with accessing data in several information system silos and performing multiple manual validation steps of data content. Notable recommendations included enhancing systems integration to create "one-stop shopping" for data, and developing a capability to perform trends analysis. Our gap analysis suggests that analytics platforms designed for surgical and ICU patients should employ approaches similar to those being used for primary care patients.

Altered Integration of Structural Covariance Networks in Young Children With Type 1 Diabetes.

Science.gov (United States)

Hosseini, S M Hadi; Mazaika, Paul; Mauras, Nelly; Buckingham, Bruce; Weinzimer, Stuart A; Tsalikian, Eva; White, Neil H; Reiss, Allan L

2016-11-01

Type 1 diabetes mellitus (T1D), one of the most frequent chronic diseases in children, is associated with glucose dysregulation that contributes to an increased risk for neurocognitive deficits. While there is a bulk of evidence regarding neurocognitive deficits in adults with T1D, little is known about how early-onset T1D affects neural networks in young children. Recent data demonstrated widespread alterations in regional gray matter and white matter associated with T1D in young children. These widespread neuroanatomical changes might impact the organization of large-scale brain networks. In the present study, we applied graph-theoretical analysis to test whether the organization of structural covariance networks in the brain for a cohort of young children with T1D (N = 141) is altered compared to healthy controls (HC; N = 69). While the networks in both groups followed a small world organization-an architecture that is simultaneously highly segregated and integrated-the T1D network showed significantly longer path length compared with HC, suggesting reduced global integration of brain networks in young children with T1D. In addition, network robustness analysis revealed that the T1D network model showed more vulnerability to neural insult compared with HC. These results suggest that early-onset T1D negatively impacts the global organization of structural covariance networks and influences the trajectory of brain development in childhood. This is the first study to examine structural covariance networks in young children with T1D. Improving glycemic control for young children with T1D might help prevent alterations in brain networks in this population. Hum Brain Mapp 37:4034-4046, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

POINeT: protein interactome with sub-network analysis and hub prioritization

Directory of Open Access Journals (Sweden)

Lai Jin-Mei

2009-04-01

Full Text Available Abstract Background Protein-protein interactions (PPIs are critical to every aspect of biological processes. Expansion of all PPIs from a set of given queries often results in a complex PPI network lacking spatiotemporal consideration. Moreover, the reliability of available PPI resources, which consist of low- and high-throughput data, for network construction remains a significant challenge. Even though a number of software tools are available to facilitate PPI network analysis, an integrated tool is crucial to alleviate the burden on querying across multiple web servers and software tools. Results We have constructed an integrated web service, POINeT, to simplify the process of PPI searching, analysis, and visualization. POINeT merges PPI and tissue-specific expression data from multiple resources. The tissue-specific PPIs and the numbers of research papers supporting the PPIs can be filtered with user-adjustable threshold values and are dynamically updated in the viewer. The network constructed in POINeT can be readily analyzed with, for example, the built-in centrality calculation module and an integrated network viewer. Nodes in global networks can also be ranked and filtered using various network analysis formulas, i.e., centralities. To prioritize the sub-network, we developed a ranking filtered method (S3 to uncover potential novel mediators in the midbody network. Several examples are provided to illustrate the functionality of POINeT. The network constructed from four schizophrenia risk markers suggests that EXOC4 might be a novel marker for this disease. Finally, a liver-specific PPI network has been filtered with adult and fetal liver expression profiles. Conclusion The functionalities provided by POINeT are highly improved compared to previous version of POINT. POINeT enables the identification and ranking of potential novel genes involved in a sub-network. Combining with tissue-specific gene expression profiles, PPIs specific to

Integrative analysis of lncRNAs and miRNAs with coding RNAs associated with ceRNA crosstalk network in triple negative breast cancer

Directory of Open Access Journals (Sweden)

Yuan NJ

2017-12-01

Full Text Available Naijun Yuan,1,* Guijuan Zhang,2,* Fengjie Bie,1 Min Ma,1 Yi Ma,3 Xuefeng Jiang,1 Yurong Wang,1,* Xiaoqian Hao1 1College of Traditional Chinese Medicine of Jinan University, Institute of Integrated Traditional Chinese and Western Medicine of Jinan University, 2The First Affiliated Hospital of Jinan University, 3Department of Cellular Biology, Guangdong Province Key Lab of Bioengineering Medicine, Institute of Biomedicine, Jinan University, Guangdong, China *These authors contributed equally to this work Abstract: Triple negative breast cancer (TNBC is a particular subtype of breast malignant tumor with poorer prognosis than other molecular subtypes. Currently, there is increasing focus on long non-coding RNAs (lncRNAs, which can act as competing endogenous RNAs (ceRNAs and suppress miRNA functions involved in post-transcriptional regulatory networks in the tumor. Therefore, to investigate specific mechanisms of TNBC carcinogenesis and improve treatment efficiency, we comprehensively integrated expression profiles, including data on mRNAs, lncRNAs and miRNAs obtained from 116 TNBC tissues and 11 normal tissues from The Cancer Genome Atlas. As a result, we selected the threshold with |log2FC|>2.0 and an adjusted p-value >0.05 to obtain the differentially expressed mRNAs, miRNAs and lncRNAs. Hereafter, weighted gene co-expression network analysis was performed to identify the expression characteristics of dysregulated genes. We obtained five co-expression modules and related clinical feature. By means of correlating gene modules with protein–protein interaction network analysis that had identified 22 hub mRNAs which could as hub target genes. Eleven key dysregulated differentially expressed micro RNAs (DEmiRNAs were identified that were significantly associated with the 22 hub potential target genes. Moreover, we found that 14 key differentially expressed lncRNAs could interact with the key DEmiRNAs. Then, the ceRNA crosstalk network of TNBC was

The use of social network analysis to examine the transmission of Salmonella spp. within a vertically integrated broiler enterprise.

Science.gov (United States)

Crabb, Helen Kathleen; Allen, Joanne Lee; Devlin, Joanne Maree; Firestone, Simon Matthew; Stevenson, Mark Anthony; Gilkerson, James Rudkin

2018-05-01

To better understand factors influencing infectious agent dispersal within a livestock population information is needed on the nature and frequency of contacts between farm enterprises. This study uses social network analysis to describe the contact network within a vertically integrated broiler poultry enterprise to identify the potential horizontal and vertical transmission pathways for Salmonella spp. Nodes (farms, sheds, production facilities) were identified and the daily movement of commodities (eggs, birds, feed, litter) and people between nodes were extracted from routinely kept farm records. Three time periods were examined in detail, 1- and 8- and 17-weeks of the production cycle and contact networks were described for all movements, and by commodity and production type. All nodes were linked by at least one movement during the study period but network density was low indicating that all potential pathways between nodes did not exist. Salmonella spp. transmission via vertical or horizontal pathways can only occur along directed pathways when those pathways are present. Only two locations (breeder or feed nodes) were identified where the transmission of a single Salmonella spp. clone could theoretically percolate through the network to the broiler or processing nodes. Only the feed transmission pathway directly connected all parts of the network. Copyright © 2017 Elsevier Ltd. All rights reserved.

TNF-α inhibits trophoblast integration into endothelial cellular networks.

Science.gov (United States)

Xu, B; Nakhla, S; Makris, A; Hennessy, A

2011-03-01

Preeclampsia has been linked to shallow trophoblast invasion and failure of uterine spiral artery transformation. Interaction between trophoblast cells and maternal uterine endothelium is critically important for this remodelling. The aim of our study was to investigate the effect of TNF-α on the interactions of trophoblast-derived JEG-3 cells into capillary-like cellular networks. We have employed an in vitro trophoblast-endothelial cell co-culture model to quantify trophoblast integration into endothelial cellular networks and to investigate the effects of TNF-α. Controlled co-cultures were also treated with anti-TNF-α antibody (5 μg/ml) to specifically block the effect of TNF-α. The invasion was evaluated by performing quantitative PCR (Q-PCR) to analyse gene expression of matrix metalloproteinases-2 (MMP-2), MMP-9, tissue inhibitor of matrix metalloproteinase (TIMP)-1, integrins (α(1)β(1) and α(6)β(4)), plasminogen activator inhibitor (PAI)-1, E-cadherin and VE-cadherin. JEG-3 cell integration into endothelial networks was significantly inhibited by exogenous TNF-α. The inhibition was observed in the range of 0.2-5 ng/ml, to a maximum 56% inhibition at the highest concentration. This inhibition was reversed by anti-TNF-α antibody. Q-PCR analysis showed that mRNA expression of integrins α(1)β(1) and MMP-2 was significantly decreased. VE-cadherin mRNA expression was significantly up-regulated (32-80%, p integration into maternal endothelial cellular networks, and this process involves the inhibition of MMP-2 and a failure of integrins switch from α(6)β(4) to α(1)β(1.) These molecular correlations reflect the changes identified in human preeclampsia. Copyright © 2011 Elsevier Ltd. All rights reserved.

A study of integration for I and C network prototype of KNGR

International Nuclear Information System (INIS)

Yang, S. K; Park, H. S.; Jeong, H. Y.

1999-01-01

Full digitization of instrumentation and control system (I and C) based on the network is one of the distinguished design characteristics of Korean Next Generation Reactor (KNGR). However, as the reliability of digital I and C system tends to depend on the reliability of software and network, developing of integrated I and C network prototype is required to verify system integrity. To achieve this goal, some prototypes of I and C systems were already developed during KNGR(II). Also, during the period of KNGR(III), integrated I and C network prototypes will be designed by prototypes developed at the stage of KNGR(II). In this paper, it will be considered to develop prototypes of plant major system and to detail the characteristics of architecture for integrated I and C network. Also, the major role of gate-way (Information Gate-Way) and backbone network will be considered too. Through this, the integrity of network design of KNGR will be achieved

A reliability analysis tool for SpaceWire network

Science.gov (United States)

Zhou, Qiang; Zhu, Longjiang; Fei, Haidong; Wang, Xingyou

2017-04-01

A SpaceWire is a standard for on-board satellite networks as the basis for future data-handling architectures. It is becoming more and more popular in space applications due to its technical advantages, including reliability, low power and fault protection, etc. High reliability is the vital issue for spacecraft. Therefore, it is very important to analyze and improve the reliability performance of the SpaceWire network. This paper deals with the problem of reliability modeling and analysis with SpaceWire network. According to the function division of distributed network, a reliability analysis method based on a task is proposed, the reliability analysis of every task can lead to the system reliability matrix, the reliability result of the network system can be deduced by integrating these entire reliability indexes in the matrix. With the method, we develop a reliability analysis tool for SpaceWire Network based on VC, where the computation schemes for reliability matrix and the multi-path-task reliability are also implemented. By using this tool, we analyze several cases on typical architectures. And the analytic results indicate that redundancy architecture has better reliability performance than basic one. In practical, the dual redundancy scheme has been adopted for some key unit, to improve the reliability index of the system or task. Finally, this reliability analysis tool will has a directive influence on both task division and topology selection in the phase of SpaceWire network system design.

Modeling integrated cellular machinery using hybrid Petri-Boolean networks.

Directory of Open Access Journals (Sweden)

Natalie Berestovsky

Full Text Available The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them

Integrated System for Performance Monitoring of ATLAS TDAQ Network

CERN Document Server

Savu, D; The ATLAS collaboration; Martin, B; Sjoen, R; Batraneanu, S; Stancu, S

2010-01-01

The ATLAS TDAQ Network consists of three separate networks spanning four levels of the experimental building. Over 200 edge switches and 5 multi-blade chassis routers are used to interconnect 2000 processors, adding up to more than 7000 high speed interfaces. In order to substantially speed-up ad-hoc and post mortem analysis, a scalable, yet flexible, integrated system for monitoring both network statistics and environmental conditions, processor parameters and data taking characteristics was required. For successful up-to-the-minute monitoring, information from many SNMP compliant devices, independent databases and custom APIs was gathered, stored and displayed in an optimal way. Easy navigation and compact aggregation of multiple data sources were the main requirements; characteristics not found in any of the tested products, either open-source or commercial. This paper describes how performance, scalability and display issues were addressed and what challenges the project faced during development and deplo...

Value Systems Alignment Analysis in Collaborative Networked Organizations Management

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Patricia Macedo

2017-11-01

Full Text Available The assessment of value systems alignment can play an important role in the formation and evolution of collaborative networks, contributing to reduce potential risks of collaboration. For this purpose, an assessment tool is proposed as part of a collaborative networks information system, supporting both the formation and evolution of long-term strategic alliances and goal-oriented networks. An implementation approach for value system alignment analysis is described, which is intended to assist managers in virtual and networked organizations management. The implementation of the assessment and analysis methods is supported by a set of software services integrated in the information system that supports the management of the networked organizations. A case study in the solar energy sector was conducted, and the data collected through this study allow us to confirm the practical applicability of the proposed methods and the software services.

Cytogenomic Integrative Network Analysis of the Critical Region Associated with Wolf-Hirschhorn Syndrome

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Thiago Corrêa

2018-01-01

Full Text Available Deletions in the 4p16.3 region are associated with Wolf-Hirschhorn syndrome (WHS, a contiguous gene deletion syndrome involving variable size deletions. In this study, we perform a cytogenomic integrative analysis combining classical cytogenetic methods, fluorescence in situ hybridization (FISH, chromosomal microarray analysis (CMA, and systems biology strategies, to establish the cytogenomic profile involving the 4p16.3 critical region and suggest WHS-related intracellular cell signaling cascades. The cytogenetic and clinical patient profiles were evaluated. We characterized 12 terminal deletions, one interstitial deletion, two ring chromosomes, and one classical translocation 4;8. CMA allowed delineation of the deletions, which ranged from 3.7 to 25.6 Mb with breakpoints from 4p16.3 to 4p15.33. Furthermore, the smallest region of overlapping (SRO encompassed seven genes in a terminal region of 330 kb in the 4p16.3 region, suggesting a region of susceptibility to convulsions and microcephaly. Therefore, molecular interaction networks and topological analysis were performed to understand these WHS-related symptoms. Our results suggest that specific cell signaling pathways including dopamine receptor, NAD+ nucleosidase activity, and fibroblast growth factor-activated receptor activity are associated with the diverse pathological WHS phenotypes and their symptoms. Additionally, we identified 29 hub-bottlenecks (H-B nodes with a major role in WHS.

PHIDIAS: a pathogen-host interaction data integration and analysis system

OpenAIRE

Xiang, Zuoshuang; Tian, Yuying; He, Yongqun

2007-01-01

The Pathogen-Host Interaction Data Integration and Analysis System (PHIDIAS) is a web-based database system that serves as a centralized source to search, compare, and analyze integrated genome sequences, conserved domains, and gene expression data related to pathogen-host interactions (PHIs) for pathogen species designated as high priority agents for public health and biological security. In addition, PHIDIAS allows submission, search and analysis of PHI genes and molecular networks curated ...

The integration of weighted gene association networks based on information entropy.

Science.gov (United States)

Yang, Fan; Wu, Duzhi; Lin, Limei; Yang, Jian; Yang, Tinghong; Zhao, Jing

2017-01-01

Constructing genome scale weighted gene association networks (WGAN) from multiple data sources is one of research hot spots in systems biology. In this paper, we employ information entropy to describe the uncertain degree of gene-gene links and propose a strategy for data integration of weighted networks. We use this method to integrate four existing human weighted gene association networks and construct a much larger WGAN, which includes richer biology information while still keeps high functional relevance between linked gene pairs. The new WGAN shows satisfactory performance in disease gene prediction, which suggests the reliability of our integration strategy. Compared with existing integration methods, our method takes the advantage of the inherent characteristics of the component networks and pays less attention to the biology background of the data. It can make full use of existing biological networks with low computational effort.

Loss of integrity and atrophy in cingulate structural covariance networks in Parkinson's disease.

Science.gov (United States)

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

2017-01-01

In Parkinson's disease (PD), the relation between cortical brain atrophy on MRI and clinical progression is not straightforward. Determination of changes in structural covariance networks - patterns of covariance in grey matter density - has shown to be a valuable technique to detect subtle grey matter variations. We evaluated how structural network integrity in PD is related to clinical data. 3 Tesla MRI was performed in 159 PD patients. We used nine standardized structural covariance networks identified in 370 healthy subjects as a template in the analysis of the PD data. Clinical assessment comprised motor features (Movement Disorder Society-Unified Parkinson's Disease Rating Scale; MDS-UPDRS motor scale) and predominantly non-dopaminergic features (SEverity of Non-dopaminergic Symptoms in Parkinson's Disease; SENS-PD scale: postural instability and gait difficulty, psychotic symptoms, excessive daytime sleepiness, autonomic dysfunction, cognitive impairment and depressive symptoms). Voxel-based analyses were performed within networks significantly associated with PD. The anterior and posterior cingulate network showed decreased integrity, associated with the SENS-PD score, p = 0.001 (β = - 0.265, η p 2  = 0.070) and p = 0.001 (β = - 0.264, η p 2  = 0.074), respectively. Of the components of the SENS-PD score, cognitive impairment and excessive daytime sleepiness were associated with atrophy within both networks. We identified loss of integrity and atrophy in the anterior and posterior cingulate networks in PD patients. Abnormalities of both networks were associated with predominantly non-dopaminergic features, specifically cognition and excessive daytime sleepiness. Our findings suggest that (components of) the cingulate networks display a specific vulnerability to the pathobiology of PD and may operate as interfaces between networks involved in cognition and alertness.

On the area spectral efficiency improvement of heterogeneous network by exploiting the integration of macro-femto cellular networks

KAUST Repository

Shakir, Muhammad

2012-06-01

Heterogeneous networks are an attractive means of expanding mobile network capacity. A heterogeneous network is typically composed of multiple radio access technologies (RATs) where the base stations are transmitting with variable power. In this paper, we consider a Heterogeneous network where we complement the macrocell network with low-power low-cost user deployed nodes, such as femtocell base stations to increase the mean achievable capacity of the system. In this context, we integrate macro-femto cellular networks and derive the area spectral efficiency of the proposed two tier Heterogeneous network. We consider the deployment of femtocell base stations around the edge of the macrocell such that this configuration is referred to as femto-on-edge (FOE) configuration. Moreover, FOE configuration mandates reduction in intercell interference due to the mobile users which are located around the edge of the macrocell since these femtocell base stations are low-power nodes which has significantly lower transmission power than macrocell base stations. We present a mathematical analysis to calculate the instantaneous carrier to interference ratio (CIR) of the desired mobile user in macro and femto cellular networks and determine the total area spectral efficiency of the Heterogeneous network. Details of the simulation processes are included to support the analysis and show the efficacy of the proposed deployment. It has been shown that the proposed setup of the Heterogeneous network offers higher area spectral efficiency which aims to fulfill the expected demand of the future mobile users. © 2012 IEEE.

T-SDN architecture for space and ground integrated optical transport network

Science.gov (United States)

Nie, Kunkun; Hu, Wenjing; Gao, Shenghua; Chang, Chengwu

2015-11-01

Integrated optical transport network is the development trend of the future space information backbone network. The space and ground integrated optical transport network(SGIOTN) may contain a variety of equipment and systems. Changing the network or meeting some innovation missions in the network will be an expensive implement. Software Defined Network(SDN) provides a good solution to flexibly adding process logic, timely control states and resources of the whole network, as well as shielding the differences of heterogeneous equipment and so on. According to the characteristics of SGIOTN, we propose an transport SDN architecture for it, with hierarchical control plane and data plane composed of packet networks and optical transport networks.

Abnormal functional integration across core brain networks in migraine without aura.

Science.gov (United States)

Yu, Dahua; Yuan, Kai; Luo, Lin; Zhai, Jinquan; Bi, Yanzhi; Xue, Ting; Ren, Xiaoying; Zhang, Ming; Ren, Guoyin; Lu, Xiaoqi

2017-01-01

As a complex subjective experience, pain processing may be related to functional integration among intrinsic connectivity networks of migraine patients without aura. However, few study focused on the pattern alterations in the intrinsic connectivity networks of migraine patients without aura. Thirty-one migraine patients without aura and 31 age- and education-matched healthy controls participated in this study. After identifying the default mode network, central executive network and salience network as core intrinsic connectivity networks by using independent component analysis, functional connectivity, and effective connectivity during the resting state were used to investigate the abnormalities in intrinsic connectivity network interactions. Migraine patients without aura showed decreased functional connectivity among intrinsic connectivity networks compared with healthy controls. The strength of causal influences from the right frontoinsular cortex to the right anterior cingulate cortex became weaker, and the right frontoinsular cortex to the right medial prefrontal cortex became stronger in migraine patients without aura. These changes suggested that the salience network may play a major role in the pathophysiological features of migraine patients without aura and helped us to synthesize previous findings into an aberrant network dynamical framework.

Integration and the performance of healthcare networks: do integration strategies enhance efficiency, profitability, and image?

Directory of Open Access Journals (Sweden)

Thomas T.H. Wan

2001-06-01

Full Text Available Purpose: This study examines the integration effects on efficiency and financial viability of the top 100 integrated healthcare networks (IHNs in the United States. Theory: A contingency- strategic theory is used to identify the relationship of IHNs' performance to their structural and operational characteristics and integration strategies. Methods: The lists of the top 100 IHNs ranked in two years, 1998 and 1999, by the SMG Marketing Group were merged to create a database for the study. Multiple indicators were used to examine the relationship between IHNs' characteristics and their performance in efficiency and financial viability. A path analytical model was developed and validated by the Mplus statistical program. Factors influencing the top 100 IHNs' images, represented by attaining ranking among the top 100 in two consecutive years, were analysed. Results and conclusion: No positive associations were found between integration and network performance in efficiency or profits. Longitudinal data are needed to investigate the effect of integration on healthcare networks' financial performance.

An Integrative Bioinformatics Framework for Genome-scale Multiple Level Network Reconstruction of Rice

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Liu Lili

2013-06-01

Full Text Available Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs, protein-protein interactions (PPIs and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

Semantic integration to identify overlapping functional modules in protein interaction networks

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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.

Integration of genomic information with biological networks using Cytoscape.

Science.gov (United States)

Bauer-Mehren, Anna

2013-01-01

Cytoscape is an open-source software for visualizing, analyzing, and modeling biological networks. This chapter explains how to use Cytoscape to analyze the functional effect of sequence variations in the context of biological networks such as protein-protein interaction networks and signaling pathways. The chapter is divided into five parts: (1) obtaining information about the functional effect of sequence variation in a Cytoscape readable format, (2) loading and displaying different types of biological networks in Cytoscape, (3) integrating the genomic information (SNPs and mutations) with the biological networks, and (4) analyzing the effect of the genomic perturbation onto the network structure using Cytoscape built-in functions. Finally, we briefly outline how the integrated data can help in building mathematical network models for analyzing the effect of the sequence variation onto the dynamics of the biological system. Each part is illustrated by step-by-step instructions on an example use case and visualized by many screenshots and figures.

Pathway cross-talk network analysis identifies critical pathways in neonatal sepsis.

Science.gov (United States)

Meng, Yu-Xiu; Liu, Quan-Hong; Chen, Deng-Hong; Meng, Ying

2017-06-01

Despite advances in neonatal care, sepsis remains a major cause of morbidity and mortality in neonates worldwide. Pathway cross-talk analysis might contribute to the inference of the driving forces in bacterial sepsis and facilitate a better understanding of underlying pathogenesis of neonatal sepsis. This study aimed to explore the critical pathways associated with the progression of neonatal sepsis by the pathway cross-talk analysis. By integrating neonatal transcriptome data with known pathway data and protein-protein interaction data, we systematically uncovered the disease pathway cross-talks and constructed a disease pathway cross-talk network for neonatal sepsis. Then, attract method was employed to explore the dysregulated pathways associated with neonatal sepsis. To determine the critical pathways in neonatal sepsis, rank product (RP) algorithm, centrality analysis and impact factor (IF) were introduced sequentially, which synthetically considered the differential expression of genes and pathways, pathways cross-talks and pathway parameters in the network. The dysregulated pathways with the highest IF values as well as RPpathways in neonatal sepsis. By integrating three kinds of data, only 6919 common genes were included to perform the pathway cross-talk analysis. By statistic analysis, a total of 1249 significant pathway cross-talks were selected to construct the pathway cross-talk network. Moreover, 47 dys-regulated pathways were identified via attract method, 20 pathways were identified under RPpathways with the highest IF were also screened from the pathway cross-talk network. Among them, we selected 8 common pathways, i.e. critical pathways. In this study, we systematically tracked 8 critical pathways involved in neonatal sepsis by integrating attract method and pathway cross-talk network. These pathways might be responsible for the host response in infection, and of great value for advancing diagnosis and therapy of neonatal sepsis. Copyright © 2017

Social Network Analysis and Qualitative Interviews for Assessing Geographic Characteristics of Tourism Business Networks.

Science.gov (United States)

Kelman, Ilan; Luthe, Tobias; Wyss, Romano; Tørnblad, Silje H; Evers, Yvette; Curran, Marina Martin; Williams, Richard J; Berlow, Eric L

2016-01-01

This study integrates quantitative social network analysis (SNA) and qualitative interviews for understanding tourism business links in isolated communities through analysing spatial characteristics. Two case studies are used, the Surselva-Gotthard region in the Swiss Alps and Longyearbyen in the Arctic archipelago of Svalbard, to test the spatial characteristics of physical proximity, isolation, and smallness for understanding tourism business links. In the larger Surselva-Gotthard region, we found a strong relationship between geographic separation of the three communities on compartmentalization of the collaboration network. A small set of businesses played a central role in steering collaborative decisions for this community, while a group of structurally 'peripheral' actors were less influential. By contrast, the business community in Svalbard showed compartmentalization that was independent of geographic distance between actors. Within towns of similar size and governance scale, Svalbard is more compartmentalized, and those compartments are not driven by geographic separation of the collaboration clusters. This compartmentalization in Svalbard was reflected in a lower density of formal business collaboration ties compared to the communities of the Alps. We infer that the difference is due to Svalbard having higher cultural diversity and population turnover than the Alps communities. We propose that integrating quantitative network analysis from simple surveys with qualitative interviews targeted from the network results is an efficient general approach to identify regionally specific constraints and opportunities for effective governance.

Social Network Analysis and Qualitative Interviews for Assessing Geographic Characteristics of Tourism Business Networks.

Directory of Open Access Journals (Sweden)

Ilan Kelman

Full Text Available This study integrates quantitative social network analysis (SNA and qualitative interviews for understanding tourism business links in isolated communities through analysing spatial characteristics. Two case studies are used, the Surselva-Gotthard region in the Swiss Alps and Longyearbyen in the Arctic archipelago of Svalbard, to test the spatial characteristics of physical proximity, isolation, and smallness for understanding tourism business links. In the larger Surselva-Gotthard region, we found a strong relationship between geographic separation of the three communities on compartmentalization of the collaboration network. A small set of businesses played a central role in steering collaborative decisions for this community, while a group of structurally 'peripheral' actors were less influential. By contrast, the business community in Svalbard showed compartmentalization that was independent of geographic distance between actors. Within towns of similar size and governance scale, Svalbard is more compartmentalized, and those compartments are not driven by geographic separation of the collaboration clusters. This compartmentalization in Svalbard was reflected in a lower density of formal business collaboration ties compared to the communities of the Alps. We infer that the difference is due to Svalbard having higher cultural diversity and population turnover than the Alps communities. We propose that integrating quantitative network analysis from simple surveys with qualitative interviews targeted from the network results is an efficient general approach to identify regionally specific constraints and opportunities for effective governance.

Social Network Analysis and Qualitative Interviews for Assessing Geographic Characteristics of Tourism Business Networks

Science.gov (United States)

Luthe, Tobias; Wyss, Romano; Tørnblad, Silje H.; Evers, Yvette; Curran, Marina Martin; Williams, Richard J.; Berlow, Eric L.

2016-01-01

This study integrates quantitative social network analysis (SNA) and qualitative interviews for understanding tourism business links in isolated communities through analysing spatial characteristics. Two case studies are used, the Surselva-Gotthard region in the Swiss Alps and Longyearbyen in the Arctic archipelago of Svalbard, to test the spatial characteristics of physical proximity, isolation, and smallness for understanding tourism business links. In the larger Surselva-Gotthard region, we found a strong relationship between geographic separation of the three communities on compartmentalization of the collaboration network. A small set of businesses played a central role in steering collaborative decisions for this community, while a group of structurally ‘peripheral’ actors were less influential. By contrast, the business community in Svalbard showed compartmentalization that was independent of geographic distance between actors. Within towns of similar size and governance scale, Svalbard is more compartmentalized, and those compartments are not driven by geographic separation of the collaboration clusters. This compartmentalization in Svalbard was reflected in a lower density of formal business collaboration ties compared to the communities of the Alps. We infer that the difference is due to Svalbard having higher cultural diversity and population turnover than the Alps communities. We propose that integrating quantitative network analysis from simple surveys with qualitative interviews targeted from the network results is an efficient general approach to identify regionally specific constraints and opportunities for effective governance. PMID:27258007

Design and development of computerized local and overall country's environmental data analysis network system

International Nuclear Information System (INIS)

Kim, Chang Gyu; Kang, Jong Gyu; Han, H.; Han, J. S.; Lee, Y. D.; Lee, S. R.; Kang, D. J.; Cho, Y. G.; Yun, S. H.

2001-03-01

In this development, we designed a integrated database for efficient data processing of radiation-environment data and developed the CLEAN (Computerized Local and overall country's Environmental data Analysis Network) system. The CLEAN system consists of local radiation-environment network, data analysis system, data open system. We developed the CLEAN system focused on building an integrated database, a data mart, and a CLEAN web site. It is expected that the developed system, which organizes the information related to environmental radiation data systematically, can be utilize for the accurate interpretation, analysis and evaluation

Artificial neural network for violation analysis

International Nuclear Information System (INIS)

Zhang, Z.; Polet, P.; Vanderhaegen, F.; Millot, P.

2004-01-01

Barrier removal (BR) is a safety-related violation, and it can be analyzed in terms of benefits, costs, and potential deficits. In order to allow designers to integrate BR into the risk analysis during the initial design phase or during re-design work, we propose a connectionist method integrating self-organizing maps (SOM). The basic SOM is an artificial neural network that, on the basis of the information contained in a multi-dimensional space, generates a space of lesser dimensions. Three algorithms--Unsupervised SOM, Supervised SOM, and Hierarchical SOM--have been developed to permit BR classification and prediction in terms of the different criteria. The proposed method can be used, on the one hand, to foresee/predict the possibility level of a new/changed barrier (prospective analysis), and on the other hand, to synthetically regroup/rearrange the BR of a given human-machine system (retrospective analysis). We applied this method to the BR analysis of an experimental railway simulator, and our preliminary results are presented here

Predicting Protein Function via Semantic Integration of Multiple Networks.

Science.gov (United States)

Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

2016-01-01

Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

Accurate path integration in continuous attractor network models of grid cells.

Science.gov (United States)

Burak, Yoram; Fiete, Ila R

2009-02-01

Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of approximately 10-100 meters and approximately 1-10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other.

Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data

NARCIS (Netherlands)

Kümmel, Anne; Panke, Sven; Heinemann, Matthias

2006-01-01

As one of the most recent members of the omics family, large-scale quantitative metabolomics data are currently complementing our systems biology data pool and offer the chance to integrate the metabolite level into the functional analysis of cellular networks. Network-embedded thermodynamic

Integration versus Outsourcing in Stable Industry Equilibrium with Communication Networks

OpenAIRE

Okamoto, Yusuke

2006-01-01

For the selection of a firm's structure between vertical integration and arm's-length outsourcing, the importance of the thickness of the market had been emphasized in the previous literature. Here we take account of communication networks such as telephone, telex, fax, and the Internet. By doing so, we could illustrate the relationship between communication networks and the make-or-buy decision. With communication network technology differing in each type of firm, both vertically integrated ...

Classification Method in Integrated Information Network Using Vector Image Comparison

Directory of Open Access Journals (Sweden)

Zhou Yuan

2014-05-01

Full Text Available Wireless Integrated Information Network (WMN consists of integrated information that can get data from its surrounding, such as image, voice. To transmit information, large resource is required which decreases the service time of the network. In this paper we present a Classification Approach based on Vector Image Comparison (VIC for WMN that improve the service time of the network. The available methods for sub-region selection and conversion are also proposed.

Changes in the topology of gene expression networks by human immunodeficiency virus type 1 (HIV-1) integration in macrophages.

Science.gov (United States)

Soto-Girón, María Juliana; García-Vallejo, Felipe

2012-01-01

One key step of human immunodeficiency virus type 1 (HIV-1) infection is the integration of its viral cDNA. This process is mediated through complex networks of host-virus interactions that alter several normal cell functions of the host. To study the complexity of disturbances in cell gene expression networks by HIV-1 integration, we constructed a network of human macrophage genes located close to chromatin regions rich in proviruses. To perform the network analysis, we selected 28 genes previously identified as the target of cDNA integration and their transcriptional profiles were obtained from GEO Profiles (NCBI). A total of 2770 interactions among the 28 genes located around the HIV-1 proviruses in human macrophages formed a highly dense main network connected to five sub-networks. The overall network was significantly enriched by genes associated with signal transduction, cellular communication and regulatory processes. To simulate the effects of HIV-1 integration in infected macrophages, five genes with the most number of interaction in the normal network were turned off by putting in zero the correspondent expression values. The HIV-1 infected network showed changes in its topology and alteration in the macrophage functions reflected in a re-programming of biosynthetic and general metabolic process. Understanding the complex virus-host interactions that occur during HIV-1 integration, may provided valuable genomic information to develop new antiviral treatments focusing on the management of some specific gene expression networks associated with viral integration. This is the first gene network which describes the human macrophages genes interactions related with HIV-1 integration. Copyright © 2011 Elsevier B.V. All rights reserved.

Impacts of optimal energy storage deployment and network reconfiguration on renewable integration level in distribution systems

International Nuclear Information System (INIS)

Santos, Sérgio F.; Fitiwi, Desta Z.; Cruz, Marco R.M.; Cabrita, Carlos M.P.; Catalão, João P.S.

2017-01-01

Highlights: • A dynamic and multi-objective stochastic mixed integer linear programming model is developed. • A new mechanism to quantify the impacts of network flexibility and ESS deployments on RES integration is presented. • Optimal integration of ESSs dramatically increases the level and the optimal exploitation of renewable DGs. • As high as 90% of RES integration level may be possible in distribution network systems. • Joint DG and ESS installations along with optimal network reconfiguration greatly contribute to voltage stability. - Abstract: Nowadays, there is a wide consensus about integrating more renewable energy sources-RESs to solve a multitude of global concerns such as meeting an increasing demand for electricity, reducing energy security and heavy dependence on fossil fuels for energy production, and reducing the overall carbon footprint of power production. Framed in this context, the coordination of RES integration with energy storage systems (ESSs), along with the network’s switching capability and/or reinforcement, is expected to significantly improve system flexibility, thereby increasing the capability of the system in accommodating large-scale RES power. Hence, this paper presents a novel mechanism to quantify the impacts of network switching and/or reinforcement as well as deployment of ESSs on the level of renewable power integrated in the system. To carry out this analysis, a dynamic and multi-objective stochastic mixed integer linear programming (S-MILP) model is developed, which jointly takes the optimal deployment of RES-based DGs and ESSs into account in coordination with distribution network reinforcement and/or reconfiguration. The IEEE 119-bus test system is used as a case study. Numerical results clearly show the capability of ESS deployment in dramatically increasing the level of renewable DGs integrated in the system. Although case-dependent, the impact of network reconfiguration on RES power integration is not

Integrated network for structural integrity monitoring of critical components in nuclear facilities, RIMIS

International Nuclear Information System (INIS)

Roth, Maria; Constantinescu, Dan Mihai; Brad, Sebastian; Ducu, Catalin; Malinovschi, Viorel

2008-01-01

The round table aims to join specialists working in the research area of the Romanian R and D Institutes and Universities involved in structural integrity assessment of materials, especially those working in the nuclear field, together with the representatives of the end user, the Cernavoda NPP. This scientific event will offer the opportunity to disseminate the theoretical, experimental and modelling activities, carried out to date, in the framework of the National Program 'Research of Excellence', Module I 2006-2008, managed by the National Authority for Scientific Research. Entitled 'Integrated Network for Structural Integrity Monitoring of Critical Components in Nuclear Facilities, RIMIS, the project has two main objectives: 1. - to elaborate a procedure applicable to the structural integrity assessment of critical components used in Romanian nuclear facilities (CANDU type Reactor, Hydrogen Isotopes Separation installations); 2. - to integrate the national networking into a similar one of European level, and to enhance the scientific significance of Romanian R and D organisations as well as to increase the contribution in solving major issues of the nuclear field. The topics of the round table will be focused on: 1. Development of a Structural Integrity Assessment Methodology applicable to the nuclear facilities components; 2. Experimental investigation methods and procedures; 3. Numeric simulation of nuclear components behaviour; 4. Further activities to finalize the assessment procedure. Also participations and contributions to sustain the activity in the European Network NULIFE, FP6 will be discussed. (authors)

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...

Ubiquitous Integrity via Network Integration and Parallelism—Sustaining Pedestrian/Bike Urbanism

Directory of Open Access Journals (Sweden)

Li-Yen Hsu

2013-08-01

Full Text Available Nowadays, due to the concern regarding environmental issues, establishing pedestrian/bike friendly urbanism is widely encouraged. To promote safety-assured, mobile communication environments, efficient, reliable maintenance, and information integrity need to be designed, especially in highly possibly interfered places. For busy traffic areas, regular degree-3 dedicated short range communication (DSRC networks are safety and information featured with availability, reliability, and maintainability in paths of multi-lanes. For sparsely populated areas, probes of wireless sensors are rational, especially if sensor nodes can be organized to enhance security, reliability, and flexibility. Applying alternative network topologies, such as spider-webs, generalized honeycomb tori, and cube-connected cycles, for comparing and analyzing is proposed in DSRC and cellular communications to enhance integrity in communications.

Integrating text mining, data mining, and network analysis for identifying genetic breast cancer trends.

Science.gov (United States)

Jurca, Gabriela; Addam, Omar; Aksac, Alper; Gao, Shang; Özyer, Tansel; Demetrick, Douglas; Alhajj, Reda

2016-04-26

Breast cancer is a serious disease which affects many women and may lead to death. It has received considerable attention from the research community. Thus, biomedical researchers aim to find genetic biomarkers indicative of the disease. Novel biomarkers can be elucidated from the existing literature. However, the vast amount of scientific publications on breast cancer make this a daunting task. This paper presents a framework which investigates existing literature data for informative discoveries. It integrates text mining and social network analysis in order to identify new potential biomarkers for breast cancer. We utilized PubMed for the testing. We investigated gene-gene interactions, as well as novel interactions such as gene-year, gene-country, and abstract-country to find out how the discoveries varied over time and how overlapping/diverse are the discoveries and the interest of various research groups in different countries. Interesting trends have been identified and discussed, e.g., different genes are highlighted in relationship to different countries though the various genes were found to share functionality. Some text analysis based results have been validated against results from other tools that predict gene-gene relations and gene functions.

Integrated computer network high-speed parallel interface

International Nuclear Information System (INIS)

Frank, R.B.

1979-03-01

As the number and variety of computers within Los Alamos Scientific Laboratory's Central Computer Facility grows, the need for a standard, high-speed intercomputer interface has become more apparent. This report details the development of a High-Speed Parallel Interface from conceptual through implementation stages to meet current and future needs for large-scle network computing within the Integrated Computer Network. 4 figures

Seamless integrated network system for wireless communication systems

NARCIS (Netherlands)

Wu, Gang; Mizuno, Mitsuhiko; Hase, Yoshihiro; Havinga, Paul J.M.

2006-01-01

To create a network that connects a plurality of wireless communication systems to create optimal systems for various environments, and that seamlessly integrates the resulting systems together in order to provide more efficient and advanced service in general. A network system that can seamlessly

Seamless integrated network system for wireless communication systems

NARCIS (Netherlands)

Wu, Gang; Mizuno, Mitsuhiko; Hase, Yoshihiro; Havinga, Paul J.M.

2002-01-01

To create a network that connects a plurality of wireless communication systems to create optimal systems for various environments, and that seamlessly integrates the resulting systems together in order to provide more efficient and advanced service in general. A network system that can seamlessly

The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

Science.gov (United States)

Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.

2010-01-01

The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624

Urban energy consumption: Different insights from energy flow analysis, input–output analysis and ecological network analysis

International Nuclear Information System (INIS)

Chen, Shaoqing; Chen, Bin

2015-01-01

Highlights: • Urban energy consumption was assessed from three different perspectives. • A new concept called controlled energy was developed from network analysis. • Embodied energy and controlled energy consumption of Beijing were compared. • The integration of all three perspectives will elucidate sustainable energy use. - Abstract: Energy consumption has always been a central issue for sustainable urban assessment and planning. Different forms of energy analysis can provide various insights for energy policy making. This paper brought together three approaches for energy consumption accounting, i.e., energy flow analysis (EFA), input–output analysis (IOA) and ecological network analysis (ENA), and compared their different perspectives and the policy implications for urban energy use. Beijing was used to exemplify the different energy analysis processes, and the 42 economic sectors of the city were aggregated into seven components. It was determined that EFA quantifies both the primary and final energy consumption of the urban components by tracking the different types of fuel used by the urban economy. IOA accounts for the embodied energy consumption (direct and indirect) used to produce goods and services in the city, whereas the control analysis of ENA quantifies the specific embodied energy that is regulated by the activities within the city’s boundary. The network control analysis can also be applied to determining which economic sectors drive the energy consumption and to what extent these sectors are dependent on each other for energy. So-called “controlled energy” is a new concept that adds to the analysis of urban energy consumption, indicating the adjustable energy consumed by sectors. The integration of insights from all three accounting perspectives further our understanding of sustainable energy use in cities

Construction of functional linkage gene networks by data integration.

Science.gov (United States)

Linghu, Bolan; Franzosa, Eric A; Xia, Yu

2013-01-01

Networks of functional associations between genes have recently been successfully used for gene function and disease-related research. A typical approach for constructing such functional linkage gene networks (FLNs) is based on the integration of diverse high-throughput functional genomics datasets. Data integration is a nontrivial task due to the heterogeneous nature of the different data sources and their variable accuracy and completeness. The presence of correlations between data sources also adds another layer of complexity to the integration process. In this chapter we discuss an approach for constructing a human FLN from data integration and a subsequent application of the FLN to novel disease gene discovery. Similar approaches can be applied to nonhuman species and other discovery tasks.

Network architectures and protocols for the integration of ACTS and ISDN

Science.gov (United States)

Chitre, D. M.; Lowry, P. A.

1992-01-01

A close integration of satellite networks and the integrated services digital network (ISDN) is essential for satellite networks to carry ISDN traffic effectively. This also shows how a given (pre-ISDN) satellite network architecture can be enhanced to handle ISDN signaling and provide ISDN services. It also describes the functional architecture and high-level protocols that could be implemented in the NASA Advanced Communications Technology Satellite (ACTS) low burst rate communications system to provide ISDN services.

Integrated workflows for spiking neuronal network simulations

Directory of Open Access Journals (Sweden)

Ján eAntolík

2013-12-01

Full Text Available The increasing availability of computational resources is enabling more detailed, realistic modelling in computational neuroscience, resulting in a shift towards more heterogeneous models of neuronal circuits, and employment of complex experimental protocols. This poses a challenge for existing tool chains, as the set of tools involved in a typical modeller's workflow is expanding concomitantly, with growing complexity in the metadata flowing between them. For many parts of the workflow, a range of tools is available; however, numerous areas lack dedicated tools, while integration of existing tools is limited. This forces modellers to either handle the workflow manually, leading to errors, or to write substantial amounts of code to automate parts of the workflow, in both cases reducing their productivity.To address these issues, we have developed Mozaik: a workflow system for spiking neuronal network simulations written in Python. Mozaik integrates model, experiment and stimulation specification, simulation execution, data storage, data analysis and visualisation into a single automated workflow, ensuring that all relevant metadata are available to all workflow components. It is based on several existing tools, including PyNN, Neo and Matplotlib. It offers a declarative way to specify models and recording configurations using hierarchically organised configuration files. Mozaik automatically records all data together with all relevant metadata about the experimental context, allowing automation of the analysis and visualisation stages. Mozaik has a modular architecture, and the existing modules are designed to be extensible with minimal programming effort. Mozaik increases the productivity of running virtual experiments on highly structured neuronal networks by automating the entire experimental cycle, while increasing the reliability of modelling studies by relieving the user from manual handling of the flow of metadata between the individual

Integrated Job Scheduling and Network Routing

DEFF Research Database (Denmark)

Gamst, Mette; Pisinger, David

2013-01-01

We consider an integrated job scheduling and network routing problem which appears in Grid Computing and production planning. The problem is to schedule a number of jobs at a finite set of machines, such that the overall profit of the executed jobs is maximized. Each job demands a number of resou...... indicate that the algorithm can be used as an actual scheduling algorithm in the Grid or as a tool for analyzing Grid performance when adding extra machines or jobs. © 2012 Wiley Periodicals, Inc.......We consider an integrated job scheduling and network routing problem which appears in Grid Computing and production planning. The problem is to schedule a number of jobs at a finite set of machines, such that the overall profit of the executed jobs is maximized. Each job demands a number...... of resources which must be sent to the executing machine through a network with limited capacity. A job cannot start before all of its resources have arrived at the machine. The scheduling problem is formulated as a Mixed Integer Program (MIP) and proved to be NP-hard. An exact solution approach using Dantzig...

Integrative mining of traditional Chinese medicine literature and MEDLINE for functional gene networks.

Science.gov (United States)

Zhou, Xuezhong; Liu, Baoyan; Wu, Zhaohui; Feng, Yi

2007-10-01

The amount of biomedical data in different disciplines is growing at an exponential rate. Integrating these significant knowledge sources to generate novel hypotheses for systems biology research is difficult. Traditional Chinese medicine (TCM) is a completely different discipline, and is a complementary knowledge system to modern biomedical science. This paper uses a significant TCM bibliographic literature database in China, together with MEDLINE, to help discover novel gene functional knowledge. We present an integrative mining approach to uncover the functional gene relationships from MEDLINE and TCM bibliographic literature. This paper introduces TCM literature (about 50,000 records) as one knowledge source for constructing literature-based gene networks. We use the TCM diagnosis, TCM syndrome, to automatically congregate the related genes. The syndrome-gene relationships are discovered based on the syndrome-disease relationships extracted from TCM literature and the disease-gene relationships in MEDLINE. Based on the bubble-bootstrapping and relation weight computing methods, we have developed a prototype system called MeDisco/3S, which has name entity and relation extraction, and online analytical processing (OLAP) capabilities, to perform the integrative mining process. We have got about 200,000 syndrome-gene relations, which could help generate syndrome-based gene networks, and help analyze the functional knowledge of genes from syndrome perspective. We take the gene network of Kidney-Yang Deficiency syndrome (KYD syndrome) and the functional analysis of some genes, such as CRH (corticotropin releasing hormone), PTH (parathyroid hormone), PRL (prolactin), BRCA1 (breast cancer 1, early onset) and BRCA2 (breast cancer 2, early onset), to demonstrate the preliminary results. The underlying hypothesis is that the related genes of the same syndrome will have some biological functional relationships, and will constitute a functional network. This paper presents

Multi-attribute integrated measurement of node importance in complex networks.

Science.gov (United States)

Wang, Shibo; Zhao, Jinlou

2015-11-01

The measure of node importance in complex networks is very important to the research of networks stability and robustness; it also can ensure the security of the whole network. Most researchers have used a single indicator to measure the networks node importance, so that the obtained measurement results only reflect certain aspects of the networks with a loss of information. Meanwhile, because of the difference of networks topology, the nodes' importance should be described by combining the character of the networks topology. Most of the existing evaluation algorithms cannot completely reflect the circumstances of complex networks, so this paper takes into account the degree of centrality, the relative closeness centrality, clustering coefficient, and topology potential and raises an integrated measuring method to measure the nodes' importance. This method can reflect nodes' internal and outside attributes and eliminate the influence of network structure on the node importance. The experiments of karate network and dolphin network show that networks topology structure integrated measure has smaller range of metrical result than a single indicator and more universal. Experiments show that attacking the North American power grid and the Internet network with the method has a faster convergence speed than other methods.

Layered signaling regulatory networks analysis of gene expression involved in malignant tumorigenesis of non-resolving ulcerative colitis via integration of cross-study microarray profiles.

Science.gov (United States)

Fan, Shengjun; Pan, Zhenyu; Geng, Qiang; Li, Xin; Wang, Yefan; An, Yu; Xu, Yan; Tie, Lu; Pan, Yan; Li, Xuejun

2013-01-01

Ulcerative colitis (UC) was the most frequently diagnosed inflammatory bowel disease (IBD) and closely linked to colorectal carcinogenesis. By far, the underlying mechanisms associated with the disease are still unclear. With the increasing accumulation of microarray gene expression profiles, it is profitable to gain a systematic perspective based on gene regulatory networks to better elucidate the roles of genes associated with disorders. However, a major challenge for microarray data analysis is the integration of multiple-studies generated by different groups. In this study, firstly, we modeled a signaling regulatory network associated with colorectal cancer (CRC) initiation via integration of cross-study microarray expression data sets using Empirical Bayes (EB) algorithm. Secondly, a manually curated human cancer signaling map was established via comprehensive retrieval of the publicly available repositories. Finally, the co-differently-expressed genes were manually curated to portray the layered signaling regulatory networks. Overall, the remodeled signaling regulatory networks were separated into four major layers including extracellular, membrane, cytoplasm and nucleus, which led to the identification of five core biological processes and four signaling pathways associated with colorectal carcinogenesis. As a result, our biological interpretation highlighted the importance of EGF/EGFR signaling pathway, EPO signaling pathway, T cell signal transduction and members of the BCR signaling pathway, which were responsible for the malignant transition of CRC from the benign UC to the aggressive one. The present study illustrated a standardized normalization approach for cross-study microarray expression data sets. Our model for signaling networks construction was based on the experimentally-supported interaction and microarray co-expression modeling. Pathway-based signaling regulatory networks analysis sketched a directive insight into colorectal carcinogenesis

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

Science.gov (United States)

Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

2015-01-01

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

PharmDB-K: Integrated Bio-Pharmacological Network Database for Traditional Korean Medicine.

Directory of Open Access Journals (Sweden)

Ji-Hyun Lee

Full Text Available Despite the growing attention given to Traditional Medicine (TM worldwide, there is no well-known, publicly available, integrated bio-pharmacological Traditional Korean Medicine (TKM database for researchers in drug discovery. In this study, we have constructed PharmDB-K, which offers comprehensive information relating to TKM-associated drugs (compound, disease indication, and protein relationships. To explore the underlying molecular interaction of TKM, we integrated fourteen different databases, six Pharmacopoeias, and literature, and established a massive bio-pharmacological network for TKM and experimentally validated some cases predicted from the PharmDB-K analyses. Currently, PharmDB-K contains information about 262 TKMs, 7,815 drugs, 3,721 diseases, 32,373 proteins, and 1,887 side effects. One of the unique sets of information in PharmDB-K includes 400 indicator compounds used for standardization of herbal medicine. Furthermore, we are operating PharmDB-K via phExplorer (a network visualization software and BioMart (a data federation framework for convenient search and analysis of the TKM network. Database URL: http://pharmdb-k.org, http://biomart.i-pharm.org.

The Contribution of Network Organization and Integration to the Development of Cognitive Control.

Science.gov (United States)

Marek, Scott; Hwang, Kai; Foran, William; Hallquist, Michael N; Luna, Beatriz

2015-12-01

Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI), graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10-26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control.

The Contribution of Network Organization and Integration to the Development of Cognitive Control

Science.gov (United States)

Marek, Scott; Hwang, Kai; Foran, William; Hallquist, Michael N.; Luna, Beatriz

2015-01-01

Abstract Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI), graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10–26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control. PMID:26713863

The Contribution of Network Organization and Integration to the Development of Cognitive Control.

Directory of Open Access Journals (Sweden)

Scott Marek

2015-12-01

Full Text Available Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI, graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10-26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control.

Integrating wireless sensor network for monitoring subsidence phenomena

Science.gov (United States)

Marturià, Jordi; Lopez, Ferran; Gigli, Giovanni; Intrieri, Emanuele; Mucchi, Lorenzo; Fornaciai, Alessandro

2016-04-01

An innovative wireless sensor network (WSN) for the 3D superficial monitoring of deformations (such as landslides and subsidence) is being developed in the frame of the Wi-GIM project (Wireless sensor network for Ground Instability Monitoring - LIFE12 ENV/IT/001033). The surface movement is detected acquiring the position (x, y and z) by integrating large bandwidth technology able to detect the 3D coordinates of the sensor with a sub-meter error, with continuous wave radar, which allows decreasing the error down to sub-cm. The Estació neighborhood in Sallent is located over the old potassium mine Enrique. This zone has been affected by a subsidence process over more than twenty years. The implementation of a wide network for ground auscultation has allowed monitoring the process of subsidence since 1997. This network consists of: i) a high-precision topographic leveling network to control the subsidence in surface; ii) a rod extensometers network to monitor subsurface deformation; iii) an automatic Leica TCA Total Station to monitor building movements; iv) an inclinometers network to measure the horizontal displacements on subsurface and v) a piezometer to measure the water level. Those networks were implemented within an alert system for an organized an efficient response of the civil protection authorities in case of an emergency. On 23rd December 2008, an acceleration of subsoil movements (of approx. 12-18 cm/year) provoked the activation of the emergency plan by the Catalan Civil Protection. This implied the preventive and scheduled evacuation of the neighbours (January 2009) located in the area with a higher risk of collapse: around 120 residents of 43 homes. As a consequence, the administration implemented a compensation plan for the evacuation of the whole neighbourhood residents and the demolition of 405 properties. In this work, the adaptation and integration process of Wi-GIM system with those conventional monitoring network are presented for its testing

Finding influential nodes for integration in brain networks using optimal percolation theory.

Science.gov (United States)

Del Ferraro, Gino; Moreno, Andrea; Min, Byungjoon; Morone, Flaviano; Pérez-Ramírez, Úrsula; Pérez-Cervera, Laura; Parra, Lucas C; Holodny, Andrei; Canals, Santiago; Makse, Hernán A

2018-06-11

Global integration of information in the brain results from complex interactions of segregated brain networks. Identifying the most influential neuronal populations that efficiently bind these networks is a fundamental problem of systems neuroscience. Here, we apply optimal percolation theory and pharmacogenetic interventions in vivo to predict and subsequently target nodes that are essential for global integration of a memory network in rodents. The theory predicts that integration in the memory network is mediated by a set of low-degree nodes located in the nucleus accumbens. This result is confirmed with pharmacogenetic inactivation of the nucleus accumbens, which eliminates the formation of the memory network, while inactivations of other brain areas leave the network intact. Thus, optimal percolation theory predicts essential nodes in brain networks. This could be used to identify targets of interventions to modulate brain function.

Data-driven integration of genome-scale regulatory and metabolic network models

Science.gov (United States)

Imam, Saheed; Schäuble, Sascha; Brooks, Aaron N.; Baliga, Nitin S.; Price, Nathan D.

2015-01-01

Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert—a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system. PMID:25999934

Computer-aided-engineering system for modeling and analysis of ECLSS integration testing

Science.gov (United States)

Sepahban, Sonbol

1987-01-01

The accurate modeling and analysis of two-phase fluid networks found in environmental control and life support systems is presently undertaken by computer-aided engineering (CAE) techniques whose generalized fluid dynamics package can solve arbitrary flow networks. The CAE system for integrated test bed modeling and analysis will also furnish interfaces and subsystem/test-article mathematical models. Three-dimensional diagrams of the test bed are generated by the system after performing the requisite simulation and analysis.

TTEthernet for Integrated Spacecraft Networks

Science.gov (United States)

Loveless, Andrew

2015-01-01

Aerospace projects have traditionally employed federated avionics architectures, in which each computer system is designed to perform one specific function (e.g. navigation). There are obvious downsides to this approach, including excessive weight (from so much computing hardware), and inefficient processor utilization (since modern processors are capable of performing multiple tasks). There has therefore been a push for integrated modular avionics (IMA), in which common computing platforms can be leveraged for different purposes. This consolidation of multiple vehicle functions to shared computing platforms can significantly reduce spacecraft cost, weight, and design complexity. However, the application of IMA principles introduces significant challenges, as the data network must accommodate traffic of mixed criticality and performance levels - potentially all related to the same shared computer hardware. Because individual network technologies are rarely so competent, the development of truly integrated network architectures often proves unreasonable. Several different types of networks are utilized - each suited to support a specific vehicle function. Critical functions are typically driven by precise timing loops, requiring networks with strict guarantees regarding message latency (i.e. determinism) and fault-tolerance. Alternatively, non-critical systems generally employ data networks prioritizing flexibility and high performance over reliable operation. Switched Ethernet has seen widespread success filling this role in terrestrial applications. Its high speed, flexibility, and the availability of inexpensive commercial off-the-shelf (COTS) components make it desirable for inclusion in spacecraft platforms. Basic Ethernet configurations have been incorporated into several preexisting aerospace projects, including both the Space Shuttle and International Space Station (ISS). However, classical switched Ethernet cannot provide the high level of network

Design of energy efficient optical networks with software enabled integrated control plane

DEFF Research Database (Denmark)

Wang, Jiayuan; Yan, Ying; Dittmann, Lars

2015-01-01

energy consumption by proposing a new integrated control plane structure utilising Software Defined Networking technologies. The integrated control plane increases the efficiencies of exchanging control information across different network domains, while introducing new possibilities to the routing...... methods and the control over quality of service (QoS). The structure is defined as an overlay generalised multi-protocol label switching (GMPLS) control model. With the defined structure, the integrated control plane is able to gather information from different domains (i.e. optical core network......'s) routing behaviours. With the flexibility of the routing structure, results show that the energy efficiency of the network can be improved without compromising the QoS for delay/blocking sensitive services....

Cost-Based Vertical Handover Decision Algorithm for WWAN/WLAN Integrated Networks

Directory of Open Access Journals (Sweden)

Kim LaeYoung

2009-01-01

Full Text Available Abstract Next generation wireless communications are expected to rely on integrated networks consisting of multiple wireless technologies. Heterogeneous networks based on Wireless Local Area Networks (WLANs and Wireless Wide Area Networks (WWANs can combine their respective advantages on coverage and data rates, offering a high Quality of Service (QoS to mobile users. In such environment, multi-interface terminals should seamlessly switch from one network to another in order to obtain improved performance or at least to maintain a continuous wireless connection. Therefore, network selection algorithm is important in providing better performance to the multi-interface terminals in the integrated networks. In this paper, we propose a cost-based vertical handover decision algorithm that triggers the Vertical Handover (VHO based on a cost function for WWAN/WLAN integrated networks. For the cost function, we focus on developing an analytical model of the expected cost of WLAN for the mobile users that enter the double-coverage area while having a connection in the WWAN. Our simulation results show that the proposed scheme achieves better performance in terms of power consumption and throughput than typical approach where WLANs are always preferred whenever the WLAN access is available.

Simulated, Emulated, and Physical Investigative Analysis (SEPIA) of networked systems.

Energy Technology Data Exchange (ETDEWEB)

Burton, David P.; Van Leeuwen, Brian P.; McDonald, Michael James; Onunkwo, Uzoma A.; Tarman, Thomas David; Urias, Vincent E.

2009-09-01

This report describes recent progress made in developing and utilizing hybrid Simulated, Emulated, and Physical Investigative Analysis (SEPIA) environments. Many organizations require advanced tools to analyze their information system's security, reliability, and resilience against cyber attack. Today's security analysis utilize real systems such as computers, network routers and other network equipment, computer emulations (e.g., virtual machines) and simulation models separately to analyze interplay between threats and safeguards. In contrast, this work developed new methods to combine these three approaches to provide integrated hybrid SEPIA environments. Our SEPIA environments enable an analyst to rapidly configure hybrid environments to pass network traffic and perform, from the outside, like real networks. This provides higher fidelity representations of key network nodes while still leveraging the scalability and cost advantages of simulation tools. The result is to rapidly produce large yet relatively low-cost multi-fidelity SEPIA networks of computers and routers that let analysts quickly investigate threats and test protection approaches.

Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Antônio Dâmaso

2017-11-01

Full Text Available Power consumption is a primary interest in Wireless Sensor Networks (WSNs, and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way.

Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks

Science.gov (United States)

Dâmaso, Antônio; Maciel, Paulo

2017-01-01

Power consumption is a primary interest in Wireless Sensor Networks (WSNs), and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way. PMID:29113078

Iconic memory and parietofrontal network: fMRI study using temporal integration.

Science.gov (United States)

Saneyoshi, Ayako; Niimi, Ryosuke; Suetsugu, Tomoko; Kaminaga, Tatsuro; Yokosawa, Kazuhiko

2011-08-03

We investigated the neural basis of iconic memory using functional magnetic resonance imaging. The parietofrontal network of selective attention is reportedly relevant to readout from iconic memory. We adopted a temporal integration task that requires iconic memory but not selective attention. The results showed that the task activated the parietofrontal network, confirming that the network is involved in readout from iconic memory. We further tested a condition in which temporal integration was performed by visual short-term memory but not by iconic memory. However, no brain region revealed higher activation for temporal integration by iconic memory than for temporal integration by visual short-term memory. This result suggested that there is no localized brain region specialized for iconic memory per se.

The Integration of Epistasis Network and Functional Interactions in a GWAS Implicates RXR Pathway Genes in the Immune Response to Smallpox Vaccine.

Directory of Open Access Journals (Sweden)

Brett A McKinney

Full Text Available Although many diseases and traits show large heritability, few genetic variants have been found to strongly separate phenotype groups by genotype. Complex regulatory networks of variants and expression of multiple genes lead to small individual-variant effects and difficulty replicating the effect of any single variant in an affected pathway. Interaction network modeling of GWAS identifies effects ignored by univariate models, but population differences may still cause specific genes to not replicate. Integrative network models may help detect indirect effects of variants in the underlying biological pathway. In this study, we used gene-level functional interaction information from the Integrative Multi-species Prediction (IMP tool to reveal important genes associated with a complex phenotype through evidence from epistasis networks and pathway enrichment. We test this method for augmenting variant-based network analyses with functional interactions by applying it to a smallpox vaccine immune response GWAS. The integrative analysis spotlights the role of genes related to retinoid X receptor alpha (RXRA, which has been implicated in a previous epistasis network analysis of smallpox vaccine.

Human Systems Integration Assessment of Network Centric Command and Control

National Research Council Canada - National Science Library

Quashnock, Dee; Kelly, Richard T; Dunaway, John; Smillie, Robert J

2004-01-01

.... FORCEnet is the operational construct and architectural framework for Naval Network Centric Warfare in the information age that integrates warriors, sensors, networks, command and control, platforms...

Network analysis literacy a practical approach to the analysis of networks

CERN Document Server

Zweig, Katharina A

2014-01-01

Network Analysis Literacy focuses on design principles for network analytics projects. The text enables readers to: pose a defined network analytic question; build a network to answer the question; choose or design the right network analytic methods for a particular purpose, and more.

Unveiling network-based functional features through integration of gene expression into protein networks.

Science.gov (United States)

Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

2018-06-01

Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

PHIDIAS: a pathogen-host interaction data integration and analysis system.

Science.gov (United States)

Xiang, Zuoshuang; Tian, Yuying; He, Yongqun

2007-01-01

The Pathogen-Host Interaction Data Integration and Analysis System (PHIDIAS) is a web-based database system that serves as a centralized source to search, compare, and analyze integrated genome sequences, conserved domains, and gene expression data related to pathogen-host interactions (PHIs) for pathogen species designated as high priority agents for public health and biological security. In addition, PHIDIAS allows submission, search and analysis of PHI genes and molecular networks curated from peer-reviewed literature. PHIDIAS is publicly available at http://www.phidias.us.

Service network design of bike sharing systems analysis and optimization

CERN Document Server

Vogel, Patrick

2016-01-01

This monograph presents a tactical planning approach for service network design in metropolitan areas. Designing the service network requires the suitable aggregation of demand data as well as the anticipation of operational relocation decisions. To this end, an integrated approach of data analysis and mathematical optimization is introduced. The book also includes a case study based on real-world data to demonstrate the benefit of the proposed service network design approach. The target audience comprises primarily research experts in the field of traffic engineering, but the book may also be beneficial for graduate students.

Integrative Analysis of Genetic, Genomic, and Phenotypic Data for Ethanol Behaviors: A Network-Based Pipeline for Identifying Mechanisms and Potential Drug Targets.

Science.gov (United States)

Bogenpohl, James W; Mignogna, Kristin M; Smith, Maren L; Miles, Michael F

2017-01-01

Complex behavioral traits, such as alcohol abuse, are caused by an interplay of genetic and environmental factors, producing deleterious functional adaptations in the central nervous system. The long-term behavioral consequences of such changes are of substantial cost to both the individual and society. Substantial progress has been made in the last two decades in understanding elements of brain mechanisms underlying responses to ethanol in animal models and risk factors for alcohol use disorder (AUD) in humans. However, treatments for AUD remain largely ineffective and few medications for this disease state have been licensed. Genome-wide genetic polymorphism analysis (GWAS) in humans, behavioral genetic studies in animal models and brain gene expression studies produced by microarrays or RNA-seq have the potential to produce nonbiased and novel insight into the underlying neurobiology of AUD. However, the complexity of such information, both statistical and informational, has slowed progress toward identifying new targets for intervention in AUD. This chapter describes one approach for integrating behavioral, genetic, and genomic information across animal model and human studies. The goal of this approach is to identify networks of genes functioning in the brain that are most relevant to the underlying mechanisms of a complex disease such as AUD. We illustrate an example of how genomic studies in animal models can be used to produce robust gene networks that have functional implications, and to integrate such animal model genomic data with human genetic studies such as GWAS for AUD. We describe several useful analysis tools for such studies: ComBAT, WGCNA, and EW_dmGWAS. The end result of this analysis is a ranking of gene networks and identification of their cognate hub genes, which might provide eventual targets for future therapeutic development. Furthermore, this combined approach may also improve our understanding of basic mechanisms underlying gene x

Data-driven integration of genome-scale regulatory and metabolic network models

Directory of Open Access Journals (Sweden)

Saheed eImam

2015-05-01

Full Text Available Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription and signaling have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert – a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.

A joint classification method to integrate scientific and social networks

NARCIS (Netherlands)

Neshati, Mahmood; Asgari, Ehsaneddin; Hiemstra, Djoerd; Beigy, Hamid

In this paper, we address the problem of scientific-social network integration to find a matching relationship between members of these networks. Utilizing several name similarity patterns and contextual properties of these networks, we design a focused crawler to find high probable matching pairs,

Explicit integration of extremely stiff reaction networks: partial equilibrium methods

International Nuclear Information System (INIS)

Guidry, M W; Hix, W R; Billings, J J

2013-01-01

In two preceding papers (Guidry et al 2013 Comput. Sci. Disc. 6 015001 and Guidry and Harris 2013 Comput. Sci. Disc. 6 015002), we have shown that when reaction networks are well removed from equilibrium, explicit asymptotic and quasi-steady-state approximations can give algebraically stabilized integration schemes that rival standard implicit methods in accuracy and speed for extremely stiff systems. However, we also showed that these explicit methods remain accurate but are no longer competitive in speed as the network approaches equilibrium. In this paper, we analyze this failure and show that it is associated with the presence of fast equilibration timescales that neither asymptotic nor quasi-steady-state approximations are able to remove efficiently from the numerical integration. Based on this understanding, we develop a partial equilibrium method to deal effectively with the approach to equilibrium and show that explicit asymptotic methods, combined with the new partial equilibrium methods, give an integration scheme that can plausibly deal with the stiffest networks, even in the approach to equilibrium, with accuracy and speed competitive with that of implicit methods. Thus we demonstrate that such explicit methods may offer alternatives to implicit integration of even extremely stiff systems and that these methods may permit integration of much larger networks than have been possible before in a number of fields. (paper)

Integrated healthcare networks' performance: a growth curve modeling approach.

Science.gov (United States)

Wan, Thomas T H; Wang, Bill B L

2003-05-01

This study examines the effects of integration on the performance ratings of the top 100 integrated healthcare networks (IHNs) in the United States. A strategic-contingency theory is used to identify the relationship of IHNs' performance to their structural and operational characteristics and integration strategies. To create a database for the panel study, the top 100 IHNs selected by the SMG Marketing Group in 1998 were followed up in 1999 and 2000. The data were merged with the Dorenfest data on information system integration. A growth curve model was developed and validated by the Mplus statistical program. Factors influencing the top 100 IHNs' performance in 1998 and their subsequent rankings in the consecutive years were analyzed. IHNs' initial performance scores were positively influenced by network size, number of affiliated physicians and profit margin, and were negatively associated with average length of stay and technical efficiency. The continuing high performance, judged by maintaining higher performance scores, tended to be enhanced by the use of more managerial or executive decision-support systems. Future studies should include time-varying operational indicators to serve as predictors of network performance.

A Critical Agency Network Model for Building an Integrated Outreach Program

Science.gov (United States)

Kiyama, Judy Marquez; Lee, Jenny J.; Rhoades, Gary

2012-01-01

This study considers a distinct case of a college outreach program that integrates student affairs staff, academic administrators, and faculty across campus. The authors find that social networks and critical agency help to understand the integration of these various professionals and offer a critical agency network model of enacting change.…

Neuronal oscillations form parietal/frontal networks during contour integration.

Science.gov (United States)

Castellano, Marta; Plöchl, Michael; Vicente, Raul; Pipa, Gordon

2014-01-01

The ability to integrate visual features into a global coherent percept that can be further categorized and manipulated are fundamental abilities of the neural system. While the processing of visual information involves activation of early visual cortices, the recruitment of parietal and frontal cortices has been shown to be crucial for perceptual processes. Yet is it not clear how both cortical and long-range oscillatory activity leads to the integration of visual features into a coherent percept. Here, we will investigate perceptual grouping through the analysis of a contour categorization task, where the local elements that form contour must be linked into a coherent structure, which is then further processed and manipulated to perform the categorization task. The contour formation in our visual stimulus is a dynamic process where, for the first time, visual perception of contours is disentangled from the onset of visual stimulation or from motor preparation, cognitive processes that until now have been behaviorally attached to perceptual processes. Our main finding is that, while local and long-range synchronization at several frequencies seem to be an ongoing phenomena, categorization of a contour could only be predicted through local oscillatory activity within parietal/frontal sources, which in turn, would synchronize at gamma (>30 Hz) frequency. Simultaneously, fronto-parietal beta (13-30 Hz) phase locking forms a network spanning across neural sources that are not category specific. Both long range networks, i.e., the gamma network that is category specific, and the beta network that is not category specific, are functionally distinct but spatially overlapping. Altogether, we show that a critical mechanism underlying contour categorization involves oscillatory activity within parietal/frontal cortices, as well as its synchronization across distal cortical sites.

Integrative omics analysis. A study based on Plasmodium falciparum mRNA and protein data.

Science.gov (United States)

Tomescu, Oana A; Mattanovich, Diethard; Thallinger, Gerhard G

2014-01-01

Technological improvements have shifted the focus from data generation to data analysis. The availability of large amounts of data from transcriptomics, protemics and metabolomics experiments raise new questions concerning suitable integrative analysis methods. We compare three integrative analysis techniques (co-inertia analysis, generalized singular value decomposition and integrative biclustering) by applying them to gene and protein abundance data from the six life cycle stages of Plasmodium falciparum. Co-inertia analysis is an analysis method used to visualize and explore gene and protein data. The generalized singular value decomposition has shown its potential in the analysis of two transcriptome data sets. Integrative Biclustering applies biclustering to gene and protein data. Using CIA, we visualize the six life cycle stages of Plasmodium falciparum, as well as GO terms in a 2D plane and interpret the spatial configuration. With GSVD, we decompose the transcriptomic and proteomic data sets into matrices with biologically meaningful interpretations and explore the processes captured by the data sets. IBC identifies groups of genes, proteins, GO Terms and life cycle stages of Plasmodium falciparum. We show method-specific results as well as a network view of the life cycle stages based on the results common to all three methods. Additionally, by combining the results of the three methods, we create a three-fold validated network of life cycle stage specific GO terms: Sporozoites are associated with transcription and transport; merozoites with entry into host cell as well as biosynthetic and metabolic processes; rings with oxidation-reduction processes; trophozoites with glycolysis and energy production; schizonts with antigenic variation and immune response; gametocyctes with DNA packaging and mitochondrial transport. Furthermore, the network connectivity underlines the separation of the intraerythrocytic cycle from the gametocyte and sporozoite stages

Design and development of computerized local and overall country's environmental data analysis network system

Energy Technology Data Exchange (ETDEWEB)

Kim, Chang Gyu; Kang, Jong Gyu; Han, H.; Han, J. S.; Lee, Y. D.; Lee, S. R.; Kang, D. J.; Cho, Y. G.; Yun, S. H. [Daedeok College, Taejon (Korea, Republic of)

2001-03-15

In this development, we designed a integrated database for efficient data processing of radiation-environment data and developed the CLEAN (Computerized Local and overall country's Environmental data Analysis Network) system. The CLEAN system consists of local radiation-environment network, data analysis system, data open system. We developed the CLEAN system focused on building an integrated database, a data mart, and a CLEAN web site. It is expected that the developed system, which organizes the information related to environmental radiation data systematically, can be utilize for the accurate interpretation, analysis and evaluation.

Structure-function relationships during segregated and integrated network states of human brain functional connectivity.

Science.gov (United States)

Fukushima, Makoto; Betzel, Richard F; He, Ye; van den Heuvel, Martijn P; Zuo, Xi-Nian; Sporns, Olaf

2018-04-01

Structural white matter connections are thought to facilitate integration of neural information across functionally segregated systems. Recent studies have demonstrated that changes in the balance between segregation and integration in brain networks can be tracked by time-resolved functional connectivity derived from resting-state functional magnetic resonance imaging (rs-fMRI) data and that fluctuations between segregated and integrated network states are related to human behavior. However, how these network states relate to structural connectivity is largely unknown. To obtain a better understanding of structural substrates for these network states, we investigated how the relationship between structural connectivity, derived from diffusion tractography, and functional connectivity, as measured by rs-fMRI, changes with fluctuations between segregated and integrated states in the human brain. We found that the similarity of edge weights between structural and functional connectivity was greater in the integrated state, especially at edges connecting the default mode and the dorsal attention networks. We also demonstrated that the similarity of network partitions, evaluated between structural and functional connectivity, increased and the density of direct structural connections within modules in functional networks was elevated during the integrated state. These results suggest that, when functional connectivity exhibited an integrated network topology, structural connectivity and functional connectivity were more closely linked to each other and direct structural connections mediated a larger proportion of neural communication within functional modules. Our findings point out the possibility of significant contributions of structural connections to integrative neural processes underlying human behavior.

The integrated disease network.

Science.gov (United States)

Sun, Kai; Buchan, Natalie; Larminie, Chris; Pržulj, Nataša

2014-11-01

The growing body of transcriptomic, proteomic, metabolomic and genomic data generated from disease states provides a great opportunity to improve our current understanding of the molecular mechanisms driving diseases and shared between diseases. The use of both clinical and molecular phenotypes will lead to better disease understanding and classification. In this study, we set out to gain novel insights into diseases and their relationships by utilising knowledge gained from system-level molecular data. We integrated different types of biological data including genome-wide association studies data, disease-chemical associations, biological pathways and Gene Ontology annotations into an Integrated Disease Network (IDN), a heterogeneous network where nodes are bio-entities and edges between nodes represent their associations. We also introduced a novel disease similarity measure to infer disease-disease associations from the IDN. Our predicted associations were systemically evaluated against the Medical Subject Heading classification and a statistical measure of disease co-occurrence in PubMed. The strong correlation between our predictions and co-occurrence associations indicated the ability of our approach to recover known disease associations. Furthermore, we presented a case study of Crohn's disease. We demonstrated that our approach not only identified well-established connections between Crohn's disease and other diseases, but also revealed new, interesting connections consistent with emerging literature. Our approach also enabled ready access to the knowledge supporting these new connections, making this a powerful approach for exploring connections between diseases.

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.

A Temporal-Causal Modelling Approach to Integrated Contagion and Network Change in Social Networks

NARCIS (Netherlands)

Blankendaal, Romy; Parinussa, Sarah; Treur, Jan

2016-01-01

This paper introduces an integrated temporal-causal model for dynamics in social networks addressing the contagion principle by which states are affected mutually, and both the homophily principle and the more-becomes-more principle by which connections are adapted over time. The integrated model

Is functional integration of resting state brain networks an unspecific biomarker for working memory performance?

Science.gov (United States)

Alavash, Mohsen; Doebler, Philipp; Holling, Heinz; Thiel, Christiane M; Gießing, Carsten

2015-03-01

Is there one optimal topology of functional brain networks at rest from which our cognitive performance would profit? Previous studies suggest that functional integration of resting state brain networks is an important biomarker for cognitive performance. However, it is still unknown whether higher network integration is an unspecific predictor for good cognitive performance or, alternatively, whether specific network organization during rest predicts only specific cognitive abilities. Here, we investigated the relationship between network integration at rest and cognitive performance using two tasks that measured different aspects of working memory; one task assessed visual-spatial and the other numerical working memory. Network clustering, modularity and efficiency were computed to capture network integration on different levels of network organization, and to statistically compare their correlations with the performance in each working memory test. The results revealed that each working memory aspect profits from a different resting state topology, and the tests showed significantly different correlations with each of the measures of network integration. While higher global network integration and modularity predicted significantly better performance in visual-spatial working memory, both measures showed no significant correlation with numerical working memory performance. In contrast, numerical working memory was superior in subjects with highly clustered brain networks, predominantly in the intraparietal sulcus, a core brain region of the working memory network. Our findings suggest that a specific balance between local and global functional integration of resting state brain networks facilitates special aspects of cognitive performance. In the context of working memory, while visual-spatial performance is facilitated by globally integrated functional resting state brain networks, numerical working memory profits from increased capacities for local processing

Electric Vehicle Integration into Modern Power Networks

DEFF Research Database (Denmark)

software tools to assess the impacts resulting from the electric vehicles deployment on the steady state and dynamic operation of electricity grids, identifies strategies to mitigate them and the possibility to support simultaneously large-scale integration of renewable energy sources. New business models......Electric Vehicle Integration into Modern Power Networks provides coverage of the challenges and opportunities posed by the progressive integration of electric drive vehicles. Starting with a thorough overview of the current electric vehicle and battery state-of-the-art, this work describes dynamic...... and control management architectures, as well as the communication infrastructure required to integrate electric vehicles as active demand are presented. Finally, regulatory issues of integrating electric vehicles into modern power systems are addressed. Inspired by two courses held under the EES...

Electric Vehicle Integration into Modern Power Networks

DEFF Research Database (Denmark)

Electric Vehicle Integration into Modern Power Networks provides coverage of the challenges and opportunities posed by the progressive integration of electric drive vehicles. Starting with a thorough overview of the current electric vehicle and battery state-of-the-art, this work describes dynamic...... software tools to assess the impacts resulting from the electric vehicles deployment on the steady state and dynamic operation of electricity grids, identifies strategies to mitigate them and the possibility to support simultaneously large-scale integration of renewable energy sources. New business models...... and control management architectures, as well as the communication infrastructure required to integrate electric vehicles as active demand are presented. Finally, regulatory issues of integrating electric vehicles into modern power systems are addressed. Inspired by two courses held under the EES...

Phosphoproteomics-based systems analysis of signal transduction networks

Directory of Open Access Journals (Sweden)

Hiroko eKozuka-Hata

2012-01-01

Full Text Available Signal transduction systems coordinate complex cellular information to regulate biological events such as cell proliferation and differentiation. Although the accumulating evidence on widespread association of signaling molecules has revealed essential contribution of phosphorylation-dependent interaction networks to cellular regulation, their dynamic behavior is mostly yet to be analyzed. Recent technological advances regarding mass spectrometry-based quantitative proteomics have enabled us to describe the comprehensive status of phosphorylated molecules in a time-resolved manner. Computational analyses based on the phosphoproteome dynamics accelerate generation of novel methodologies for mathematical analysis of cellular signaling. Phosphoproteomics-based numerical modeling can be used to evaluate regulatory network elements from a statistical point of view. Integration with transcriptome dynamics also uncovers regulatory hubs at the transcriptional level. These omics-based computational methodologies, which have firstly been applied to representative signaling systems such as the epidermal growth factor receptor pathway, have now opened up a gate for systems analysis of signaling networks involved in immune response and cancer.

Integrated resource management for Hybrid Optical Wireless (HOW) networks

DEFF Research Database (Denmark)

Yan, Ying; Yu, Hao; Wessing, Henrik

2009-01-01

Efficient utilization of available bandwidth over hybrid optical wireless networks is a critical issue, especially for multimedia applications with high data rates and stringent Quality of Service (QoS) requirements. In this paper, we propose an integrated resource management including an enhanced...... resource sharing scheme and an integrated admission control scheme for the hybrid optical wireless networks. It provides QoS guarantees for connections through both optical and wireless domain. Simulation results show that our proposed scheme improves QoS performances in terms of high throughput and low...

Design mobile satellite system architecture as an integral part of the cellular access digital network

Science.gov (United States)

Chien, E. S. K.; Marinho, J. A.; Russell, J. E., Sr.

1988-01-01

The Cellular Access Digital Network (CADN) is the access vehicle through which cellular technology is brought into the mainstream of the evolving integrated telecommunications network. Beyond the integrated end-to-end digital access and per call network services provisioning of the Integrated Services Digital Network (ISDN), the CADN engenders the added capability of mobility freedom via wireless access. One key element of the CADN network architecture is the standard user to network interface that is independent of RF transmission technology. Since the Mobile Satellite System (MSS) is envisioned to not only complement but also enhance the capabilities of the terrestrial cellular telecommunications network, compatibility and interoperability between terrestrial cellular and mobile satellite systems are vitally important to provide an integrated moving telecommunications network of the future. From a network standpoint, there exist very strong commonalities between the terrestrial cellular system and the mobile satellite system. Therefore, the MSS architecture should be designed as an integral part of the CADN. This paper describes the concept of the CADN, the functional architecture of the MSS, and the user-network interface signaling protocols.

Integration of Satellite and Terrestrial Networks at JPL

Science.gov (United States)

Pinck, D. S.

1995-01-01

This presentation focuses on the activities at JPL on the integration of satellite and terrestrial networks for mobile and personal communications. Activities fall into two categories: 1)advanced systems work, and 2)laboratory and field experimentation. Results of a workshop held at JPL on PCS integration and interoperability will be presented. Experiments will be described.

Towards integrated crisis support of regional emergency networks.

Science.gov (United States)

Caro, D H

1999-01-01

Emergency and crisis management pose multidimensional information systems challenges for communities across North America. In the quest to reduce mortality and morbidity risks and to increase the level of crisis preparedness, regional emergency management networks have evolved. Integrated Crisis Support Systems (ICSS) are enabling information technologies that assist emergency managers by enhancing the ability to strategically manage and control these regional emergency networks efficiently and effectively. This article underscores the ICCS development, control and leadership issues and their promising implications for regional emergency management networks.

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks.

Science.gov (United States)

Shen, Yiwen; Hattink, Maarten H N; Samadi, Payman; Cheng, Qixiang; Hu, Ziyiz; Gazman, Alexander; Bergman, Keren

2018-04-16

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. We present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly network testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 µs control plane latency for data-center and high performance computing platforms.

Perspectives and limitations of QKD integration in metropolitan area networks.

Science.gov (United States)

Aleksic, Slavisa; Hipp, Florian; Winkler, Dominic; Poppe, Andreas; Schrenk, Bernhard; Franzl, Gerald

2015-04-20

Quantum key distribution (QKD) systems have already reached a reasonable level of maturity. However, a smooth integration and a wide adoption of commercial QKD systems in metropolitan area networks has still remained challenging because of technical and economical obstacles. Mainly the need for dedicated fibers and the strong dependence of the secret key rate on both loss budget and background noise in the quantum channel hinder a practical, flexible and robust implementation of QKD in current and next-generation optical metro networks. In this paper, we discuss these obstacles and present approaches to share existing fiber infrastructures among quantum and classical channels. Particularly, a proposal for a smooth integration of QKD in optical metro networks, which implies removing spurious background photons caused by optical transmitters, amplifiers and nonlinear effects in fibers, is presented and discussed. We determine and characterize impairments on quantum channels caused by many classical telecom channels at practically used power levels coexisting within the same fiber. Extensive experimental results are presented and indicate that a practical integration of QKD in conventional optical metro networks is possible.

Integrative Analysis of Hippocampus Gene Expression Profiles Identifies Network Alterations in Aging and Alzheimer’s Disease

Directory of Open Access Journals (Sweden)

Vinay Lanke

2018-05-01

Full Text Available Alzheimer’s disease (AD is a neurodegenerative disorder contributing to rapid decline in cognitive function and ultimately dementia. Most cases of AD occur in elderly and later years. There is a growing need for understanding the relationship between aging and AD to identify shared and unique hallmarks associated with the disease in a region and cell-type specific manner. Although genomic studies on AD have been performed extensively, the molecular mechanism of disease progression is still not clear. The major objective of our study is to obtain a higher-order network-level understanding of aging and AD, and their relationship using the hippocampal gene expression profiles of young (20–50 years, aging (70–99 years, and AD (70–99 years. The hippocampus is vulnerable to damage at early stages of AD and altered neurogenesis in the hippocampus is linked to the onset of AD. We combined the weighted gene co-expression network and weighted protein–protein interaction network-level approaches to study the transition from young to aging to AD. The network analysis revealed the organization of co-expression network into functional modules that are cell-type specific in aging and AD. We found that modules associated with astrocytes, endothelial cells and microglial cells are upregulated and significantly correlate with both aging and AD. The modules associated with neurons, mitochondria and endoplasmic reticulum are downregulated and significantly correlate with AD than aging. The oligodendrocytes module does not show significant correlation with neither aging nor disease. Further, we identified aging- and AD-specific interactions/subnetworks by integrating the gene expression with a human protein–protein interaction network. We found dysregulation of genes encoding protein kinases (FYN, SYK, SRC, PKC, MAPK1, ephrin receptors and transcription factors (FOS, STAT3, CEBPB, MYC, NFKβ, and EGR1 in AD. Further, we found genes that encode proteins

Designing optimal bioethanol networks with purification for integrated biorefineries

International Nuclear Information System (INIS)

Shenoy, Akshay U.; Shenoy, Uday V.

2014-01-01

Highlights: • An analytical method is devised for bioethanol network integration with purification. • Minimum fresh bioethanol flow and pinch are found by the Unified Targeting Algorithm. • Optimal bioethanol networks are then synthesized by the Nearest Neighbors Algorithm. • Continuous targets and networks are developed over the purifier inlet flowrate range. • Case study of a biorefinery producing bioethanol from wheat shows large savings. - Abstract: Bioethanol networks with purification for processing pathways in integrated biorefineries are targeted and designed in this work by an analytical approach not requiring graphical constructions. The approach is based on six fundamental equations involving eight variables: two balance equations for the stream flowrate and the bioethanol load over the total network system; one equation for the above-pinch bioethanol load being picked up by the minimum fresh resource and the purified stream; and three equations for the purification unit. A solution strategy is devised by specifying the two variables associated with the purifier inlet stream. Importantly, continuous targeting is then possible over the entire purifier inlet flowrate range on deriving elegant formulae for the remaining six variables. The Unified Targeting Algorithm (UTA) is utilized to establish the minimum fresh bioethanol resource flowrate and identify the pinch purity. The fresh bioethanol resource flowrate target is shown to decrease linearly with purifier inlet flowrate provided the pinch is held by the same point. The Nearest Neighbors Algorithm (NNA) is used to methodically synthesize optimal networks matching bioethanol demands and sources. A case study of a biorefinery producing bioethanol from wheat with arabinoxylan (AX) coproduction is presented. It illustrates the versatility of the approach in generating superior practical designs with up to nearly 94% savings for integrated bioethanol networks, both with and without process

Functional network integrity presages cognitive decline in preclinical Alzheimer disease.

Science.gov (United States)

Buckley, Rachel F; Schultz, Aaron P; Hedden, Trey; Papp, Kathryn V; Hanseeuw, Bernard J; Marshall, Gad; Sepulcre, Jorge; Smith, Emily E; Rentz, Dorene M; Johnson, Keith A; Sperling, Reisa A; Chhatwal, Jasmeer P

2017-07-04

To examine the utility of resting-state functional connectivity MRI (rs-fcMRI) measurements of network integrity as a predictor of future cognitive decline in preclinical Alzheimer disease (AD). A total of 237 clinically normal older adults (aged 63-90 years, Clinical Dementia Rating 0) underwent baseline β-amyloid (Aβ) imaging with Pittsburgh compound B PET and structural and rs-fcMRI. We identified 7 networks for analysis, including 4 cognitive networks (default, salience, dorsal attention, and frontoparietal control) and 3 noncognitive networks (primary visual, extrastriate visual, motor). Using linear and curvilinear mixed models, we used baseline connectivity in these networks to predict longitudinal changes in preclinical Alzheimer cognitive composite (PACC) performance, both alone and interacting with Aβ burden. Median neuropsychological follow-up was 3 years. Baseline connectivity in the default, salience, and control networks predicted longitudinal PACC decline, unlike connectivity in the dorsal attention and all noncognitive networks. Default, salience, and control network connectivity was also synergistic with Aβ burden in predicting decline, with combined higher Aβ and lower connectivity predicting the steepest curvilinear decline in PACC performance. In clinically normal older adults, lower functional connectivity predicted more rapid decline in PACC scores over time, particularly when coupled with increased Aβ burden. Among examined networks, default, salience, and control networks were the strongest predictors of rate of change in PACC scores, with the inflection point of greatest decline beyond the fourth year of follow-up. These results suggest that rs-fcMRI may be a useful predictor of early, AD-related cognitive decline in clinical research settings. © 2017 American Academy of Neurology.

Networks and network analysis for defence and security

CERN Document Server

Masys, Anthony J

2014-01-01

Networks and Network Analysis for Defence and Security discusses relevant theoretical frameworks and applications of network analysis in support of the defence and security domains. This book details real world applications of network analysis to support defence and security. Shocks to regional, national and global systems stemming from natural hazards, acts of armed violence, terrorism and serious and organized crime have significant defence and security implications. Today, nations face an uncertain and complex security landscape in which threats impact/target the physical, social, economic

Social network extraction based on Web: 3. the integrated superficial method

Science.gov (United States)

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

2018-03-01

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

Students' network integration as a predictor of persistence in introductory physics courses

Science.gov (United States)

Zwolak, Justyna P.; Dou, Remy; Williams, Eric A.; Brewe, Eric

2017-06-01

Increasing student retention (successfully finishing a particular course) and persistence (continuing through a sequence of courses or the major area of study) is currently a major challenge for universities. While students' academic and social integration into an institution seems to be vital for student retention, research into the effect of interpersonal interactions is rare. We use network analysis as an approach to investigate academic and social experiences of students in the classroom. In particular, centrality measures identify patterns of interaction that contribute to integration into the university. Using these measures, we analyze how position within a social network in a Modeling Instruction (MI) course—an introductory physics course that strongly emphasizes interactive learning—predicts their persistence in taking a subsequent physics course. Students with higher centrality at the end of the first semester of MI are more likely to enroll in a second semester of MI. Moreover, we found that chances of successfully predicting individual student's persistence based on centrality measures are fairly high—up to 75%, making the centrality a good predictor of persistence. These findings suggest that increasing student social integration may help in improving persistence in science, technology, engineering, and mathematics fields.

Antenna analysis using neural networks

Science.gov (United States)

Smith, William T.

1992-01-01

Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern

Self-organizing path integration using a linked continuous attractor and competitive network: path integration of head direction.

Science.gov (United States)

Stringer, Simon M; Rolls, Edmund T

2006-12-01

A key issue is how networks in the brain learn to perform path integration, that is update a represented position using a velocity signal. Using head direction cells as an example, we show that a competitive network could self-organize to learn to respond to combinations of head direction and angular head rotation velocity. These combination cells can then be used to drive a continuous attractor network to the next head direction based on the incoming rotation signal. An associative synaptic modification rule with a short term memory trace enables preceding combination cell activity during training to be associated with the next position in the continuous attractor network. The network accounts for the presence of neurons found in the brain that respond to combinations of head direction and angular head rotation velocity. Analogous networks in the hippocampal system could self-organize to perform path integration of place and spatial view representations.

Integrated failure probability estimation based on structural integrity analysis and failure data: Natural gas pipeline case

International Nuclear Information System (INIS)

Dundulis, Gintautas; Žutautaitė, Inga; Janulionis, Remigijus; Ušpuras, Eugenijus; Rimkevičius, Sigitas; Eid, Mohamed

2016-01-01

In this paper, the authors present an approach as an overall framework for the estimation of the failure probability of pipelines based on: the results of the deterministic-probabilistic structural integrity analysis (taking into account loads, material properties, geometry, boundary conditions, crack size, and defected zone thickness), the corrosion rate, the number of defects and failure data (involved into the model via application of Bayesian method). The proposed approach is applied to estimate the failure probability of a selected part of the Lithuanian natural gas transmission network. The presented approach for the estimation of integrated failure probability is a combination of several different analyses allowing us to obtain: the critical crack's length and depth, the failure probability of the defected zone thickness, dependency of the failure probability on the age of the natural gas transmission pipeline. A model's uncertainty analysis and uncertainty propagation analysis are performed, as well. - Highlights: • Degradation mechanisms of natural gas transmission pipelines. • Fracture mechanic analysis of the pipe with crack. • Stress evaluation of the pipe with critical crack. • Deterministic-probabilistic structural integrity analysis of gas pipeline. • Integrated estimation of pipeline failure probability by Bayesian method.

CATHENA 4. A thermalhydraulics network analysis code

International Nuclear Information System (INIS)

Aydemir, N.U.; Hanna, B.N.

2009-01-01

Canadian Algorithm for THErmalhydraulic Network Analysis (CATHENA) is a one-dimensional, non-equilibrium, two-phase, two fluid network analysis code that has been in use for over two decades by various groups in Canada and around the world. The objective of the present paper is to describe the design, application and future development plans for the CATHENA 4 thermalhydraulics network analysis code, which is a modernized version of the present frozen CATHENA 3 code. The new code is designed in modular form, using the Fortran 95 (F95) programming language. The semi-implicit numerical integration scheme of CATHENA 3 is re-written to implement a fully-implicit methodology using Newton's iterative solution scheme suitable for nonlinear equations. The closure relations, as a first step, have been converted from the existing CATHENA 3 implementation to F95 but modularized to achieve ease of maintenance. The paper presents the field equations, followed by a description of the Newton's scheme used. The finite-difference form of the field equations is given, followed by a discussion of convergence criteria. Two applications of CATHENA 4 are presented to demonstrate the temporal and spatial convergence of the new code for problems with known solutions or available experimental data. (author)

Regulatory Improvements for Effective Integration of Distributed Generation into Electricity Distribution Networks

International Nuclear Information System (INIS)

Scheepers, M.J.J.; Jansen, J.C.; De Joode, J.; Bauknecht, D.; Gomez, T.; Pudjianto, D.; Strbac, G.; Ropenus, S.

2007-11-01

The growth of distributed electricity supply of renewable energy sources (RES-E) and combined heat and power (CHP) - so called distributed generation (DG) - can cause technical problems for electricity distribution networks. These integration problems can be overcome by reinforcing the network. Many European Member States apply network regulation that does not account for the impact of DG growth on the network costs. Passing on network integration costs to the DG-operator who is responsible for these extra costs may result in discrimination between different DG plants and between DG and large power generation. Therefore, in many regulatory systems distribution system operators (DSOs) are not being compensated for the DG integration costs. The DG-GRID project analysed technical and economical barriers for integration of distributed generation into electricity distribution networks. The project looked into the impact of a high DG deployment on the electricity distribution system costs and the impact on the financial position of the DSO. Several ways for improving network regulation in order to compensate DSOs for the increasing DG penetration were identified and tested. The DG-GRID project looked also into stimulating network innovations through economic regulation. The project was co-financed by the European Commission and carried out by nine European universities and research institutes. This report summarises the project results and is based on a number of DG-GRID reports that describe the conducted analyses and their results

Impact and Cost Evaluation of Electric Vehicle Integration on Medium Voltage Distribution Networks

DEFF Research Database (Denmark)

Wu, Qiuwei; Cheng, Lin; Pineau, Ulysse

2013-01-01

This paper presents the analysis of the impact of electric vehicle (EV) integration on medium voltage (MV) distribution networks and the cost evaluation of replacing the overloaded grid components. A number of EV charging scenarios have been studied. A 10 kV grid from the Bornholm Island...... in the city area has been used to carry out case studies. The case study results show that the secondary transformers are the bottleneck of the MV distribution networks and the increase of EV penetration leads to the overloading of secondary transformers. The cost of the transformer replacement has been...

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk.

Science.gov (United States)

Kar, Siddhartha P; Tyrer, Jonathan P; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V; Bean, Yukie T; Beckmann, Matthias W; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S; Cramer, Daniel; Cunningham, Julie M; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F; Edwards, Robert P; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goode, Ellen L; Goodman, Marc T; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K; Hosono, Satoyo; Iversen, Edwin S; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; McNeish, Iain A; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Phelan, Catherine M; Pike, Malcolm C; Poole, Elizabeth M; Ramus, Susan J; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Schildkraut, Joellen M; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston-Campbell, Lara E; Tangen, Ingvild L; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S; van Altena, Anne M; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A; Monteiro, Alvaro N A; Freedman, Matthew L; Gayther, Simon A; Pharoah, Paul D P

2015-10-01

Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. ©2015 American Association for Cancer Research.

Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

Science.gov (United States)

Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

2018-04-24

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

Integration of Self-Assembled Microvascular Networks with Microfabricated PEG-Based Hydrogels.

Science.gov (United States)

Cuchiara, Michael P; Gould, Daniel J; McHale, Melissa K; Dickinson, Mary E; West, Jennifer L

2012-11-07

Despite tremendous efforts, tissue engineered constructs are restricted to thin, simple tissues sustained only by diffusion. The most significant barrier in tissue engineering is insufficient vascularization to deliver nutrients and metabolites during development in vitro and to facilitate rapid vascular integration in vivo. Tissue engineered constructs can be greatly improved by developing perfusable microvascular networks in vitro in order to provide transport that mimics native vascular organization and function. Here a microfluidic hydrogel is integrated with a self-assembling pro-vasculogenic co-culture in a strategy to perfuse microvascular networks in vitro. This approach allows for control over microvascular network self-assembly and employs an anastomotic interface for integration of self-assembled micro-vascular networks with fabricated microchannels. As a result, transport within the system shifts from simple diffusion to vessel supported convective transport and extra-vessel diffusion, thus improving overall mass transport properties. This work impacts the development of perfusable prevascularized tissues in vitro and ultimately tissue engineering applications in vivo.

Optimizing Groundwater Monitoring Networks Using Integrated Statistical and Geostatistical Approaches

Directory of Open Access Journals (Sweden)

Jay Krishna Thakur

2015-08-01

Full Text Available The aim of this work is to investigate new approaches using methods based on statistics and geo-statistics for spatio-temporal optimization of groundwater monitoring networks. The formulated and integrated methods were tested with the groundwater quality data set of Bitterfeld/Wolfen, Germany. Spatially, the monitoring network was optimized using geo-statistical methods. Temporal optimization of the monitoring network was carried out using Sen’s method (1968. For geostatistical network optimization, a geostatistical spatio-temporal algorithm was used to identify redundant wells in 2- and 2.5-D Quaternary and Tertiary aquifers. Influences of interpolation block width, dimension, contaminant association, groundwater flow direction and aquifer homogeneity on statistical and geostatistical methods for monitoring network optimization were analysed. The integrated approach shows 37% and 28% redundancies in the monitoring network in Quaternary aquifer and Tertiary aquifer respectively. The geostatistical method also recommends 41 and 22 new monitoring wells in the Quaternary and Tertiary aquifers respectively. In temporal optimization, an overall optimized sampling interval was recommended in terms of lower quartile (238 days, median quartile (317 days and upper quartile (401 days in the research area of Bitterfeld/Wolfen. Demonstrated methods for improving groundwater monitoring network can be used in real monitoring network optimization with due consideration given to influencing factors.

The Segregation and Integration of Distinct Brain Networks and Their Relationship to Cognition.

Science.gov (United States)

Cohen, Jessica R; D'Esposito, Mark

2016-11-30

A critical feature of the human brain that gives rise to complex cognition is its ability to reconfigure its network structure dynamically and adaptively in response to the environment. Existing research probing task-related reconfiguration of brain network structure has concluded that, although there are many similarities in network structure during an intrinsic, resting state and during the performance of a variety of cognitive tasks, there are meaningful differences as well. In this study, we related intrinsic, resting state network organization to reconfigured network organization during the performance of two tasks: a sequence tapping task, which is thought to probe motor execution and likely engages a single brain network, and an n-back task, which is thought to probe working memory and likely requires coordination across multiple networks. We implemented graph theoretical analyses using functional connectivity data from fMRI scans to calculate whole-brain measures of network organization in healthy young adults. We focused on quantifying measures of network segregation (modularity, system segregation, local efficiency, number of provincial hub nodes) and measures of network integration (global efficiency, number of connector hub nodes). Using these measures, we found converging evidence that local, within-network communication is critical for motor execution, whereas integrative, between-network communication is critical for working memory. These results confirm that the human brain has the remarkable ability to reconfigure its large-scale organization dynamically in response to current cognitive demands and that interpreting reconfiguration in terms of network segregation and integration may shed light on the optimal network structures underlying successful cognition. The dynamic nature of the human brain gives rise to the wide range of behaviors and cognition of which humans are capable. We collected fMRI data from healthy young adults and measured large

Fast mapping rapidly integrates information into existing memory networks.

Science.gov (United States)

Coutanche, Marc N; Thompson-Schill, Sharon L

2014-12-01

Successful learning involves integrating new material into existing memory networks. A learning procedure known as fast mapping (FM), thought to simulate the word-learning environment of children, has recently been linked to distinct neuroanatomical substrates in adults. This idea has suggested the (never-before tested) hypothesis that FM may promote rapid incorporation into cortical memory networks. We test this hypothesis here in 2 experiments. In our 1st experiment, we introduced 50 participants to 16 unfamiliar animals and names through FM or explicit encoding (EE) and tested participants on the training day, and again after sleep. Learning through EE produced strong declarative memories, without immediate lexical competition, as expected from slow-consolidation models. Learning through FM, however, led to almost immediate lexical competition, which continued to the next day. Additionally, the learned words began to prime related concepts on the day following FM (but not EE) training. In a 2nd experiment, we replicated the lexical integration results and determined that presenting an already-known item during learning was crucial for rapid integration through FM. The findings presented here indicate that learned items can be integrated into cortical memory networks at an accelerated rate through fast mapping. The retrieval of a related known concept, in order to infer the target of the FM question, is critical for this effect. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Integrated Approach to Reconstruction of Microbial Regulatory Networks

Energy Technology Data Exchange (ETDEWEB)

Rodionov, Dmitry A [Sanford-Burnham Medical Research Institute; Novichkov, Pavel S [Lawrence Berkeley National Laboratory

2013-11-04

This project had the goal(s) of development of integrated bioinformatics platform for genome-scale inference and visualization of transcriptional regulatory networks (TRNs) in bacterial genomes. The work was done in Sanford-Burnham Medical Research Institute (SBMRI, P.I. D.A. Rodionov) and Lawrence Berkeley National Laboratory (LBNL, co-P.I. P.S. Novichkov). The developed computational resources include: (1) RegPredict web-platform for TRN inference and regulon reconstruction in microbial genomes, and (2) RegPrecise database for collection, visualization and comparative analysis of transcriptional regulons reconstructed by comparative genomics. These analytical resources were selected as key components in the DOE Systems Biology KnowledgeBase (SBKB). The high-quality data accumulated in RegPrecise will provide essential datasets of reference regulons in diverse microbes to enable automatic reconstruction of draft TRNs in newly sequenced genomes. We outline our progress toward the three aims of this grant proposal, which were: Develop integrated platform for genome-scale regulon reconstruction; Infer regulatory annotations in several groups of bacteria and building of reference collections of microbial regulons; and Develop KnowledgeBase on microbial transcriptional regulation.

Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange

Science.gov (United States)

Jahangoshai Rezaee, Mustafa; Jozmaleki, Mehrdad; Valipour, Mahsa

2018-01-01

One of the main features to invest in stock exchange companies is their financial performance. On the other hand, conventional evaluation methods such as data envelopment analysis are not only a retrospective process, but are also a process, which are incomplete and ineffective approaches to evaluate the companies in the future. To remove this problem, it is required to plan an expert system for evaluating organizations when the online data are received from stock exchange market. This paper deals with an approach for predicting the online financial performance of companies when data are received in different time's intervals. The proposed approach is based on integrating fuzzy C-means (FCM), data envelopment analysis (DEA) and artificial neural network (ANN). The classical FCM method is unable to update the number of clusters and their members when the data are changed or the new data are received. Hence, this method is developed in order to make dynamic features for the number of clusters and clusters members in classical FCM. Then, DEA is used to evaluate DMUs by using financial ratios to provide targets in neural network. Finally, the designed network is trained and prepared for predicting companies' future performance. The data on Tehran Stock Market companies for six consecutive years (2007-2012) are used to show the abilities of the proposed approach.

MotifNet: a web-server for network motif analysis.

Science.gov (United States)

Smoly, Ilan Y; Lerman, Eugene; Ziv-Ukelson, Michal; Yeger-Lotem, Esti

2017-06-15

Network motifs are small topological patterns that recur in a network significantly more often than expected by chance. Their identification emerged as a powerful approach for uncovering the design principles underlying complex networks. However, available tools for network motif analysis typically require download and execution of computationally intensive software on a local computer. We present MotifNet, the first open-access web-server for network motif analysis. MotifNet allows researchers to analyze integrated networks, where nodes and edges may be labeled, and to search for motifs of up to eight nodes. The output motifs are presented graphically and the user can interactively filter them by their significance, number of instances, node and edge labels, and node identities, and view their instances. MotifNet also allows the user to distinguish between motifs that are centered on specific nodes and motifs that recur in distinct parts of the network. MotifNet is freely available at http://netbio.bgu.ac.il/motifnet . The website was implemented using ReactJs and supports all major browsers. The server interface was implemented in Python with data stored on a MySQL database. estiyl@bgu.ac.il or michaluz@cs.bgu.ac.il. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Transcription regulatory networks analysis using CAGE

KAUST Repository

Tegnér, Jesper N.

2009-10-01

Mapping out cellular networks in general and transcriptional networks in particular has proved to be a bottle-neck hampering our understanding of biological processes. Integrative approaches fusing computational and experimental technologies for decoding transcriptional networks at a high level of resolution is therefore of uttermost importance. Yet, this is challenging since the control of gene expression in eukaryotes is a complex multi-level process influenced by several epigenetic factors and the fine interplay between regulatory proteins and the promoter structure governing the combinatorial regulation of gene expression. In this chapter we review how the CAGE data can be integrated with other measurements such as expression, physical interactions and computational prediction of regulatory motifs, which together can provide a genome-wide picture of eukaryotic transcriptional regulatory networks at a new level of resolution. © 2010 by Pan Stanford Publishing Pte. Ltd. All rights reserved.

Too Many Friends: Social Integration, Network Cohesion and Adolescent Depressive Symptoms

Science.gov (United States)

Falci, Christina; McNeely, Clea

2009-01-01

Using a nationally representative sample of adolescents, we examine associations among social integration (network size), network cohesion (alter-density), perceptions of social relationships (e.g., social support) and adolescent depressive symptoms. We find that adolescents with either too large or too small a network have higher levels of…

Vertical integration and organizational networks in health care.

Science.gov (United States)

Robinson, J C; Casalino, L P

1996-01-01

This paper documents the growing linkages between primary care-centered medical groups and specialists and between physicians and hospitals under managed care. We evaluate the two alternative forms of organizational coordination: "vertical integration," based on unified ownership, and "virtual integration," based on contractual networks. Excess capacity and the need for investment capital are major short-term determinants of these vertical versus virtual integration decisions in health care. In the longer term, the principal determinants are economies of scale, risk-bearing ability, transaction costs, and the capacity for innovation in methods of managing care.

Spatial-temporal data model and fractal analysis of transportation network in GIS environment

Science.gov (United States)

Feng, Yongjiu; Tong, Xiaohua; Li, Yangdong

2008-10-01

How to organize transportation data characterized by multi-time, multi-scale, multi-resolution and multi-source is one of the fundamental problems of GIS-T development. A spatial-temporal data model for GIS-T is proposed based on Spatial-temporal- Object Model. Transportation network data is systemically managed using dynamic segmentation technologies. And then a spatial-temporal database is built to integrally store geographical data of multi-time for transportation. Based on the spatial-temporal database, functions of spatial analysis of GIS-T are substantively extended. Fractal module is developed to improve the analyzing in intensity, density, structure and connectivity of transportation network based on the validation and evaluation of topologic relation. Integrated fractal with GIS-T strengthens the functions of spatial analysis and enriches the approaches of data mining and knowledge discovery of transportation network. Finally, the feasibility of the model and methods are tested thorough Guangdong Geographical Information Platform for Highway Project.

Locally Integrated Energy Sectors supported by renewable network management within municipalities

International Nuclear Information System (INIS)

Kostevšek, Anja; Petek, Janez; Čuček, Lidija; Klemeš, Jiří Jaromír; Varbanov, Petar Sabev

2015-01-01

The decarbonisation of energy systems is one of the important issues of the present energy policies. One of the ways of achieving this is to focus on local energy systems, thus ensuring as much as possible their heat and power self-sufficiency by applying local renewable resource integration and transformation of the renewable energy. Increasing the share of renewables within the local energy balance could be accomplished by using a variety of approaches. One possibility is combining the Locally Integrated Energy Sectors' concept with the novel management and organisation of a renewables-based network. As a first priority, the proposed comprehensive approach focuses on increasing the energy efficiency of municipal heat and power systems using the Locally Integrated Energy Sectors' concept, which is followed by the integration of renewable energy sources with the establishment of a renewable-based network. The proposed approach is illustrated by a case study of district heating based on wood biomass for the municipality Ormož, Slovenia by integrating various end-users from different sectors. - Highlights: • The paper presents a new approach for accelerated inception of RES in municipalities. • LIES with RES network increases energy efficiency and accelerates RES integration. • A demonstration case of district heating on wood biomass within Ormož was performed.

Ecological network analysis on global virtual water trade.

Science.gov (United States)

Yang, Zhifeng; Mao, Xufeng; Zhao, Xu; Chen, Bin

2012-02-07

Global water interdependencies are likely to increase with growing virtual water trade. To address the issues of the indirect effects of water trade through the global economic circulation, we use ecological network analysis (ENA) to shed insight into the complicated system interactions. A global model of virtual water flow among agriculture and livestock production trade in 1995-1999 is also built as the basis for network analysis. Control analysis is used to identify the quantitative control or dependency relations. The utility analysis provides more indicators for describing the mutual relationship between two regions/countries by imitating the interactions in the ecosystem and distinguishes the beneficiary and the contributor of virtual water trade system. Results show control and utility relations can well depict the mutual relation in trade system, and direct observable relations differ from integral ones with indirect interactions considered. This paper offers a new way to depict the interrelations between trade components and can serve as a meaningful start as we continue to use ENA in providing more valuable implications for freshwater study on a global scale.

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach

Science.gov (United States)

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions. PMID:29033978

Ecological network analysis for a virtual water network.

Science.gov (United States)

Fang, Delin; Chen, Bin

2015-06-02

The notions of virtual water flows provide important indicators to manifest the water consumption and allocation between different sectors via product transactions. However, the configuration of virtual water network (VWN) still needs further investigation to identify the water interdependency among different sectors as well as the network efficiency and stability in a socio-economic system. Ecological network analysis is chosen as a useful tool to examine the structure and function of VWN and the interactions among its sectors. A balance analysis of efficiency and redundancy is also conducted to describe the robustness (RVWN) of VWN. Then, network control analysis and network utility analysis are performed to investigate the dominant sectors and pathways for virtual water circulation and the mutual relationships between pairwise sectors. A case study of the Heihe River Basin in China shows that the balance between efficiency and redundancy is situated on the left side of the robustness curve with less efficiency and higher redundancy. The forestation, herding and fishing sectors and industrial sectors are found to be the main controllers. The network tends to be more mutualistic and synergic, though some competitive relationships that weaken the virtual water circulation still exist.

The Intellectual Structure of Metacognitive Scaffolding in Science Education: A Co-Citation Network Analysis

Science.gov (United States)

Tang, Kai-Yu; Wang, Chia-Yu; Chang, Hsin-Yi; Chen, Sufen; Lo, Hao-Chang; Tsai, Chin-Chung

2016-01-01

The issues of metacognitive scaffolding in science education (MSiSE) have become increasingly popular and important. Differing from previous content reviews, this study proposes a series of quantitative computer-based analyses by integrating document co-citation analysis, social network analysis, and exploratory factor analysis to explore the…

Pathway Relevance Ranking for Tumor Samples through Network-Based Data Integration.

Directory of Open Access Journals (Sweden)

Lieven P C Verbeke

Full Text Available The study of cancer, a highly heterogeneous disease with different causes and clinical outcomes, requires a multi-angle approach and the collection of large multi-omics datasets that, ideally, should be analyzed simultaneously. We present a new pathway relevance ranking method that is able to prioritize pathways according to the information contained in any combination of tumor related omics datasets. Key to the method is the conversion of all available data into a single comprehensive network representation containing not only genes but also individual patient samples. Additionally, all data are linked through a network of previously identified molecular interactions. We demonstrate the performance of the new method by applying it to breast and ovarian cancer datasets from The Cancer Genome Atlas. By integrating gene expression, copy number, mutation and methylation data, the method's potential to identify key pathways involved in breast cancer development shared by different molecular subtypes is illustrated. Interestingly, certain pathways were ranked equally important for different subtypes, even when the underlying (epi-genetic disturbances were diverse. Next to prioritizing universally high-scoring pathways, the pathway ranking method was able to identify subtype-specific pathways. Often the score of a pathway could not be motivated by a single mutation, copy number or methylation alteration, but rather by a combination of genetic and epi-genetic disturbances, stressing the need for a network-based data integration approach. The analysis of ovarian tumors, as a function of survival-based subtypes, demonstrated the method's ability to correctly identify key pathways, irrespective of tumor subtype. A differential analysis of survival-based subtypes revealed several pathways with higher importance for the bad-outcome patient group than for the good-outcome patient group. Many of the pathways exhibiting higher importance for the bad

[Comprehensive system integration and networking in operating rooms].

Science.gov (United States)

Feußner, H; Ostler, D; Kohn, N; Vogel, T; Wilhelm, D; Koller, S; Kranzfelder, M

2016-12-01

A comprehensive surveillance and control system integrating all devices and functions is a precondition for realization of the operating room of the future. Multiple proprietary integrated operation room systems are currently available with a central user interface; however, they only cover a relatively small part of all functionalities. Internationally, there are at least three different initiatives to promote a comprehensive systems integration and networking in the operating room: the Japanese smart cyber operating theater (SCOT), the American medical device plug-and-play interoperability program (MDPnP) and the German secure and dynamic networking in operating room and hospital (OR.NET) project supported by the Federal Ministry of Education and Research. Within the framework of the internationally advanced OR.NET project, prototype solution approaches were realized, which make short-term and mid-term comprehensive data retrieval systems probable. An active and even autonomous control of the medical devices by the surveillance and control system (closed loop) is expected only in the long run due to strict regulatory barriers.

The governance of regional networks in the process of European integration

OpenAIRE

Cappellin, Riccardo

2001-01-01

The paper illustrates the model of territorial networks and it investigates the role of institutions in a bottom-up approach of economic and institutional integration aiming to tackle the negative impacts of the globalization process on the economic development. The first chapter illustrates in analytical terms the model of territorial networks and the multidimen-sional nature of the process of integration, in a regional and international setting and it contrasts it with the traditional neocl...

Representation and traversal of documentation space. Data analysis, neuron networks and image banks

International Nuclear Information System (INIS)

Lelu, A.; Rosenblatt, D.

1986-01-01

Improvements in the visual representation of considerable amounts of data for the user is necessary for progress in documentation systems. We review practical implementations in this area, which additionally integrate concepts arising from data analysis in the most general sense. The relationship between data analysis and neuron networks is then established. Following a description of simulation experiments, we finally present software for outputting and traversing image banks which integrate most of the concept developed in this article [fr

Gene Prioritization by Integrated Analysis of Protein Structural and Network Topological Properties for the Protein-Protein Interaction Network of Neurological Disorders

Directory of Open Access Journals (Sweden)

Yashna Paul

2016-01-01

Full Text Available Neurological disorders are known to show similar phenotypic manifestations like anxiety, depression, and cognitive impairment. There is a need to identify shared genetic markers and molecular pathways in these diseases, which lead to such comorbid conditions. Our study aims to prioritize novel genetic markers that might increase the susceptibility of patients affected with one neurological disorder to other diseases with similar manifestations. Identification of pathways involving common candidate markers will help in the development of improved diagnosis and treatments strategies for patients affected with neurological disorders. This systems biology study for the first time integratively uses 3D-structural protein interface descriptors and network topological properties that characterize proteins in a neurological protein interaction network, to aid the identification of genes that are previously not known to be shared between these diseases. Results of protein prioritization by machine learning have identified known as well as new genetic markers which might have direct or indirect involvement in several neurological disorders. Important gene hubs have also been identified that provide an evidence for shared molecular pathways in the neurological disease network.

MINET: transient analysis of fluid-flow and heat-transfer networks

International Nuclear Information System (INIS)

Van Tuyle, G.J.; Guppy, J.G.; Nepsee, T.C.

1983-01-01

MINET, a computer code developed for the steady-state and transient analysis of fluid-flow and heat-transfer networks, is described. The code is based on a momentum integral network method, which offers significant computational advantages in the analysis of large systems, such as the balance of plant in a power-generating facility. An application is discussed in which MINET is coupled to the Super System Code (SSC), an advanced generic code for the transient analysis of loop- or pool-type LMFBR systems. In this application, the ability of the Clinch River Breeder Reactor Plant to operate in a natural circulation mode following an assumed loss of all electric power, was assessed. Results from the MINET portion of the calculations are compared against those generated independently by the Clinch River Project, using the DEMO code

Aespoe Hard Rock Laboratory. Analysis of fracture networks based on the integration of structural and hydrogeological observations on different scales

Energy Technology Data Exchange (ETDEWEB)

Bossart, P. [Geotechnical Inst. Ltd., Bern (Switzerland); Hermanson, Jan [Golder Associates, Stockholm (Sweden); Mazurek, M. [Univ. of Bern (Switzerland)

2001-05-01

Fracture networks at Aespoe have been studied for several rock types exhibiting different degrees of ductile and brittle deformation, as well as on different scales. Mesoscopic fault systems have been characterised and classified in an earlier report, this report focuses mainly on fracture networks derived on smaller scales, but also includes mesoscopic and larger scales. The TRUE-1 block has been selected for detailed structural analysis on a small scale due to the high density of relevant information. In addition to the data obtained from core materials, structural maps, BIP data and the results of hydro tests were synthesised to derive a conceptual structural model. The approach used to derive this conceptual model is based on the integration of deterministic structural evidence, probabilistic information and both upscaling and downscaling of observations and concepts derived on different scales. Twelve fracture networks mapped at different sites and scales and exhibiting various styles of tectonic deformation were analysed for fractal properties and structural and hydraulic interconnectedness. It was shown that these analysed fracture networks are not self-similar. An important result is the structural and hydraulic interconnectedness of fracture networks on all scales in the Aespoe rocks, which is further corroborated by geochemical evidence. Due to the structural and hydraulic interconnectedness of fracture systems on all scales at Aespoe, contaminants from waste canisters placed in tectonically low deformation environments would be transported - after having passed through the engineered barriers -from low-permeability fractures towards higher permeability fractures and may thus eventually reach high-permeability features.

Aespoe Hard Rock Laboratory. Analysis of fracture networks based on the integration of structural and hydrogeological observations on different scales

International Nuclear Information System (INIS)

Bossart, P.; Hermanson, Jan; Mazurek, M.

2001-05-01

Fracture networks at Aespoe have been studied for several rock types exhibiting different degrees of ductile and brittle deformation, as well as on different scales. Mesoscopic fault systems have been characterised and classified in an earlier report, this report focuses mainly on fracture networks derived on smaller scales, but also includes mesoscopic and larger scales. The TRUE-1 block has been selected for detailed structural analysis on a small scale due to the high density of relevant information. In addition to the data obtained from core materials, structural maps, BIP data and the results of hydro tests were synthesised to derive a conceptual structural model. The approach used to derive this conceptual model is based on the integration of deterministic structural evidence, probabilistic information and both upscaling and downscaling of observations and concepts derived on different scales. Twelve fracture networks mapped at different sites and scales and exhibiting various styles of tectonic deformation were analysed for fractal properties and structural and hydraulic interconnectedness. It was shown that these analysed fracture networks are not self-similar. An important result is the structural and hydraulic interconnectedness of fracture networks on all scales in the Aespoe rocks, which is further corroborated by geochemical evidence. Due to the structural and hydraulic interconnectedness of fracture systems on all scales at Aespoe, contaminants from waste canisters placed in tectonically low deformation environments would be transported - after having passed through the engineered barriers -from low-permeability fractures towards higher permeability fractures and may thus eventually reach high-permeability features

An integrative analysis of cellular contexts, miRNAs and mRNAs reveals network clusters associated with antiestrogen-resistant breast cancer cells

Directory of Open Access Journals (Sweden)

Nam Seungyoon

2012-12-01

Full Text Available Abstract Background A major goal of the field of systems biology is to translate genome-wide profiling data (e.g., mRNAs, miRNAs into interpretable functional networks. However, employing a systems biology approach to better understand the complexities underlying drug resistance phenotypes in cancer continues to represent a significant challenge to the field. Previously, we derived two drug-resistant breast cancer sublines (tamoxifen- and fulvestrant-resistant cell lines from the MCF7 breast cancer cell line and performed genome-wide mRNA and microRNA profiling to identify differential molecular pathways underlying acquired resistance to these important antiestrogens. In the current study, to further define molecular characteristics of acquired antiestrogen resistance we constructed an “integrative network”. We combined joint miRNA-mRNA expression profiles, cancer contexts, miRNA-target mRNA relationships, and miRNA upstream regulators. In particular, to reduce the probability of false positive connections in the network, experimentally validated, rather than prediction-oriented, databases were utilized to obtain connectivity. Also, to improve biological interpretation, cancer contexts were incorporated into the network connectivity. Results Based on the integrative network, we extracted “substructures” (network clusters representing the drug resistant states (tamoxifen- or fulvestrant-resistance cells compared to drug sensitive state (parental MCF7 cells. We identified un-described network clusters that contribute to antiestrogen resistance consisting of miR-146a, -27a, -145, -21, -155, -15a, -125b, and let-7s, in addition to the previously described miR-221/222. Conclusions By integrating miRNA-related network, gene/miRNA expression and text-mining, the current study provides a computational-based systems biology approach for further investigating the molecular mechanism underlying antiestrogen resistance in breast cancer cells. In

Integration of heterogeneous molecular networks to unravel gene-regulation in Mycobacterium tuberculosis

NARCIS (Netherlands)

Dam, van J.C.J.; Schaap, P.J.; Martins dos Santos, V.A.P.; Suarez Diez, M.

2014-01-01

Background: Different methods have been developed to infer regulatory networks from heterogeneous omics datasets and to construct co-expression networks. Each algorithm produces different networks and efforts have been devoted to automatically integrate them into consensus sets. However each

Network integration modelling of feeder and BRT(bus rapid transit) to reduce the usage of private vehicles in Palembang’s suburban area

Science.gov (United States)

Nur'afalia, D.; Afifa, F.; Rubianto, L.; Handayeni, K. D. M. E.

2018-01-01

The aim of this research is to determine the optimal feeder network route that integrates with BRT (Bus Rapid Transit). Palembang, a high growing population city with unresolved transportation demand sector. BRT as main public transportation could not fulfill people’s demand in transportation, especially in Alang-Alang Lebar sub-district. As an impact, the usage of private vehicles increases along the movement toward the city center. The concept of Network Integration that integrates feeder network with BRT is expected to be a solution to suppress the rate of private vehicles’ usage and to improve public transportation service, so that the use of BRT will be increased in the suburban area of Palembang. The method used to identifying the optimal route using Route Analysis method is route analysis using Tranetsim 0.4. The best route is obtained based on 156 movement samples. The result is 58,7% from 199 mobility’s potency of private vehicle usage’s can be reduced if there is a feeder network’s route in Alang-Alang Lebar’s sub-district. From the result, the existance of integration between feeder network and BRT is potential enough to reduce the usage of private vehicles and supports the sustainability of transportation mobility in Palembang City.

Photonic integrated multiwavelength transmitters for fiber-to-the-home networks

NARCIS (Netherlands)

Lawniczuk, K.; Smit, M.K.; Piramidowicz, P.; Szczepanski, P.; Leijtens, X.J.M.; Wale, M.J.

2012-01-01

In this paper we present measurement results of monolithically integrated photonic transmitters for application in the next generation Fiber-to-the-Home (FTTH) networks. 4- and 8-channel transmitters were integrated onto a single chip, using multiple lasers with distributed Bragg reflector (DBR)

System-level Modeling of Wireless Integrated Sensor Networks

DEFF Research Database (Denmark)

Virk, Kashif M.; Hansen, Knud; Madsen, Jan

2005-01-01

Wireless integrated sensor networks have emerged as a promising infrastructure for a new generation of monitoring and tracking applications. In order to efficiently utilize the extremely limited resources of wireless sensor nodes, accurate modeling of the key aspects of wireless sensor networks...... is necessary so that system-level design decisions can be made about the hardware and the software (applications and real-time operating system) architecture of sensor nodes. In this paper, we present a SystemC-based abstract modeling framework that enables system-level modeling of sensor network behavior...... by modeling the applications, real-time operating system, sensors, processor, and radio transceiver at the sensor node level and environmental phenomena, including radio signal propagation, at the sensor network level. We demonstrate the potential of our modeling framework by simulating and analyzing a small...

Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration.

Science.gov (United States)

Arneson, Douglas; Bhattacharya, Anindya; Shu, Le; Mäkinen, Ville-Petteri; Yang, Xia

2016-09-09

Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators

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.

Content-driven analysis of an online community for smoking cessation: integration of qualitative techniques, automated text analysis, and affiliation networks.

Science.gov (United States)

Myneni, Sahiti; Fujimoto, Kayo; Cobb, Nathan; Cohen, Trevor

2015-06-01

We identified content-specific patterns of network diffusion underlying smoking cessation in the context of online platforms, with the aim of generating targeted intervention strategies. QuitNet is an online social network for smoking cessation. We analyzed 16 492 de-identified peer-to-peer messages from 1423 members, posted between March 1 and April 30, 2007. Our mixed-methods approach comprised qualitative coding, automated text analysis, and affiliation network analysis to identify, visualize, and analyze content-specific communication patterns underlying smoking behavior. Themes we identified in QuitNet messages included relapse, QuitNet-specific traditions, and cravings. QuitNet members who were exposed to other abstinent members by exchanging content related to interpersonal themes (e.g., social support, traditions, progress) tended to abstain. Themes found in other types of content did not show significant correlation with abstinence. Modeling health-related affiliation networks through content-driven methods can enable the identification of specific content related to higher abstinence rates, which facilitates targeted health promotion.

Integrating Space Communication Network Capabilities via Web Portal Technologies

Science.gov (United States)

Johnston, Mark D.; Lee, Carlyn-Ann; Lau, Chi-Wung; Cheung, Kar-Ming; Levesque, Michael; Carruth, Butch; Coffman, Adam; Wallace, Mike

2014-01-01

We have developed a service portal prototype as part of an investigation into the feasibility of using Java portlet technology as a means of providing integrated access to NASA communications network services. Portal servers provide an attractive platform for this role due to the various built-in collaboration applications they can provide, combined with the possibility to develop custom inter-operating portlets to extent their functionality while preserving common presentation and behavior. This paper describes various options for integration of network services related to planning and scheduling, and results based on use of a popular open-source portal framework. Plans are underway to develop an operational SCaN Service Portal, building on the experiences reported here.

Explicit integration with GPU acceleration for large kinetic networks

International Nuclear Information System (INIS)

Brock, Benjamin; Belt, Andrew; Billings, Jay Jay; Guidry, Mike

2015-01-01

We demonstrate the first implementation of recently-developed fast explicit kinetic integration algorithms on modern graphics processing unit (GPU) accelerators. Taking as a generic test case a Type Ia supernova explosion with an extremely stiff thermonuclear network having 150 isotopic species and 1604 reactions coupled to hydrodynamics using operator splitting, we demonstrate the capability to solve of order 100 realistic kinetic networks in parallel in the same time that standard implicit methods can solve a single such network on a CPU. This orders-of-magnitude decrease in computation time for solving systems of realistic kinetic networks implies that important coupled, multiphysics problems in various scientific and technical fields that were intractable, or could be simulated only with highly schematic kinetic networks, are now computationally feasible.

Physical explosion analysis in heat exchanger network design

Science.gov (United States)

Pasha, M.; Zaini, D.; Shariff, A. M.

2016-06-01

The failure of shell and tube heat exchangers is being extensively experienced by the chemical process industries. This failure can create a loss of production for long time duration. Moreover, loss of containment through heat exchanger could potentially lead to a credible event such as fire, explosion and toxic release. There is a need to analyse the possible worst case effect originated from the loss of containment of the heat exchanger at the early design stage. Physical explosion analysis during the heat exchanger network design is presented in this work. Baker and Prugh explosion models are deployed for assessing the explosion effect. Microsoft Excel integrated with process design simulator through object linking and embedded (OLE) automation for this analysis. Aspen HYSYS V (8.0) used as a simulation platform in this work. A typical heat exchanger network of steam reforming and shift conversion process was presented as a case study. It is investigated from this analysis that overpressure generated from the physical explosion of each heat exchanger can be estimated in a more precise manner by using Prugh model. The present work could potentially assist the design engineer to identify the critical heat exchanger in the network at the preliminary design stage.

Recurrent network models for perfect temporal integration of fluctuating correlated inputs.

Directory of Open Access Journals (Sweden)

Hiroshi Okamoto

2009-06-01

Full Text Available Temporal integration of input is essential to the accumulation of information in various cognitive and behavioral processes, and gradually increasing neuronal activity, typically occurring within a range of seconds, is considered to reflect such computation by the brain. Some psychological evidence suggests that temporal integration by the brain is nearly perfect, that is, the integration is non-leaky, and the output of a neural integrator is accurately proportional to the strength of input. Neural mechanisms of perfect temporal integration, however, remain largely unknown. Here, we propose a recurrent network model of cortical neurons that perfectly integrates partially correlated, irregular input spike trains. We demonstrate that the rate of this temporal integration changes proportionately to the probability of spike coincidences in synaptic inputs. We analytically prove that this highly accurate integration of synaptic inputs emerges from integration of the variance of the fluctuating synaptic inputs, when their mean component is kept constant. Highly irregular neuronal firing and spike coincidences are the major features of cortical activity, but they have been separately addressed so far. Our results suggest that the efficient protocol of information integration by cortical networks essentially requires both features and hence is heterotic.

Performance Analysis of a Cluster-Based MAC Protocol for Wireless Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Jesús Alonso-Zárate

2010-01-01

Full Text Available An analytical model to evaluate the non-saturated performance of the Distributed Queuing Medium Access Control Protocol for Ad Hoc Networks (DQMANs in single-hop networks is presented in this paper. DQMAN is comprised of a spontaneous, temporary, and dynamic clustering mechanism integrated with a near-optimum distributed queuing Medium Access Control (MAC protocol. Clustering is executed in a distributed manner using a mechanism inspired by the Distributed Coordination Function (DCF of the IEEE 802.11. Once a station seizes the channel, it becomes the temporary clusterhead of a spontaneous cluster and it coordinates the peer-to-peer communications between the clustermembers. Within each cluster, a near-optimum distributed queuing MAC protocol is executed. The theoretical performance analysis of DQMAN in single-hop networks under non-saturation conditions is presented in this paper. The approach integrates the analysis of the clustering mechanism into the MAC layer model. Up to the knowledge of the authors, this approach is novel in the literature. In addition, the performance of an ad hoc network using DQMAN is compared to that obtained when using the DCF of the IEEE 802.11, as a benchmark reference.

RADSS: an integration of GIS, spatial statistics, and network service for regional data mining

Science.gov (United States)

Hu, Haitang; Bao, Shuming; Lin, Hui; Zhu, Qing

2005-10-01

Regional data mining, which aims at the discovery of knowledge about spatial patterns, clusters or association between regions, has widely applications nowadays in social science, such as sociology, economics, epidemiology, crime, and so on. Many applications in the regional or other social sciences are more concerned with the spatial relationship, rather than the precise geographical location. Based on the spatial continuity rule derived from Tobler's first law of geography: observations at two sites tend to be more similar to each other if the sites are close together than if far apart, spatial statistics, as an important means for spatial data mining, allow the users to extract the interesting and useful information like spatial pattern, spatial structure, spatial association, spatial outlier and spatial interaction, from the vast amount of spatial data or non-spatial data. Therefore, by integrating with the spatial statistical methods, the geographical information systems will become more powerful in gaining further insights into the nature of spatial structure of regional system, and help the researchers to be more careful when selecting appropriate models. However, the lack of such tools holds back the application of spatial data analysis techniques and development of new methods and models (e.g., spatio-temporal models). Herein, we make an attempt to develop such an integrated software and apply it into the complex system analysis for the Poyang Lake Basin. This paper presents a framework for integrating GIS, spatial statistics and network service in regional data mining, as well as their implementation. After discussing the spatial statistics methods involved in regional complex system analysis, we introduce RADSS (Regional Analysis and Decision Support System), our new regional data mining tool, by integrating GIS, spatial statistics and network service. RADSS includes the functions of spatial data visualization, exploratory spatial data analysis, and

Social network analysis applied to team sports analysis

CERN Document Server

Clemente, Filipe Manuel; Mendes, Rui Sousa

2016-01-01

Explaining how graph theory and social network analysis can be applied to team sports analysis, This book presents useful approaches, models and methods that can be used to characterise the overall properties of team networks and identify the prominence of each team player. Exploring the different possible network metrics that can be utilised in sports analysis, their possible applications and variances from situation to situation, the respective chapters present an array of illustrative case studies. Identifying the general concepts of social network analysis and network centrality metrics, readers are shown how to generate a methodological protocol for data collection. As such, the book provides a valuable resource for students of the sport sciences, sports engineering, applied computation and the social sciences.

Process and data fragmentation-oriented enterprise network integration with collaboration modelling and collaboration agents

Science.gov (United States)

Li, Qing; Wang, Ze-yuan; Cao, Zhi-chao; Du, Rui-yang; Luo, Hao

2015-08-01

With the process of globalisation and the development of management models and information technology, enterprise cooperation and collaboration has developed from intra-enterprise integration, outsourcing and inter-enterprise integration, and supply chain management, to virtual enterprises and enterprise networks. Some midfielder enterprises begin to serve for different supply chains. Therefore, they combine related supply chains into a complex enterprise network. The main challenges for enterprise network's integration and collaboration are business process and data fragmentation beyond organisational boundaries. This paper reviews the requirements of enterprise network's integration and collaboration, as well as the development of new information technologies. Based on service-oriented architecture (SOA), collaboration modelling and collaboration agents are introduced to solve problems of collaborative management for service convergence under the condition of process and data fragmentation. A model-driven methodology is developed to design and deploy the integrating framework. An industrial experiment is designed and implemented to illustrate the usage of developed technologies in this paper.

Genetic networks of liver metabolism revealed by integration of metabolic and transcriptional profiling.

Directory of Open Access Journals (Sweden)

Christine T Ferrara

2008-03-01

Full Text Available Although numerous quantitative trait loci (QTL influencing disease-related phenotypes have been detected through gene mapping and positional cloning, identification of the individual gene(s and molecular pathways leading to those phenotypes is often elusive. One way to improve understanding of genetic architecture is to classify phenotypes in greater depth by including transcriptional and metabolic profiling. In the current study, we have generated and analyzed mRNA expression and metabolic profiles in liver samples obtained in an F2 intercross between the diabetes-resistant C57BL/6 leptin(ob/ob and the diabetes-susceptible BTBR leptin(ob/ob mouse strains. This cross, which segregates for genotype and physiological traits, was previously used to identify several diabetes-related QTL. Our current investigation includes microarray analysis of over 40,000 probe sets, plus quantitative mass spectrometry-based measurements of sixty-seven intermediary metabolites in three different classes (amino acids, organic acids, and acyl-carnitines. We show that liver metabolites map to distinct genetic regions, thereby indicating that tissue metabolites are heritable. We also demonstrate that genomic analysis can be integrated with liver mRNA expression and metabolite profiling data to construct causal networks for control of specific metabolic processes in liver. As a proof of principle of the practical significance of this integrative approach, we illustrate the construction of a specific causal network that links gene expression and metabolic changes in the context of glutamate metabolism, and demonstrate its validity by showing that genes in the network respond to changes in glutamine and glutamate availability. Thus, the methods described here have the potential to reveal regulatory networks that contribute to chronic, complex, and highly prevalent diseases and conditions such as obesity and diabetes.

Integrated Environment for Ubiquitous Healthcare and Mobile IPv6 Networks

Science.gov (United States)

Cagalaban, Giovanni; Kim, Seoksoo

The development of Internet technologies based on the IPv6 protocol will allow real-time monitoring of people with health deficiencies and improve the independence of elderly people. This paper proposed a ubiquitous healthcare system for the personalized healthcare services with the support of mobile IPv6 networks. Specifically, this paper discusses the integration of ubiquitous healthcare and wireless networks and its functional requirements. This allow an integrated environment where heterogeneous devices such a mobile devices and body sensors can continuously monitor patient status and communicate remotely with healthcare servers, physicians, and family members to effectively deliver healthcare services.

Complexity and network dynamics in physiological adaptation: an integrated view.

Science.gov (United States)

Baffy, György; Loscalzo, Joseph

2014-05-28

Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of the operational characteristics, allowing us to propose an integrated framework of physiological adaptation from a complex network perspective. Applicability of this concept is illustrated by analyzing molecular and cellular mechanisms of adaptation in response to the pervasive challenge of obesity, a chronic condition resulting from sustained nutrient excess that prompts chaotic exploration for system stability associated with tradeoffs and a risk of adverse outcomes such as diabetes, cardiovascular disease, and cancer. Deconstruction of this complexity holds the promise of gaining novel insights into physiological adaptation in health and disease. Published by Elsevier Inc.

Synergies between energy supply networks

DEFF Research Database (Denmark)

Wu, Jianzhnog; Yan, Jinyue; Desideri, Umberto

2017-01-01

Energy system integration uses a whole-system approach to optimize the synergies between energy supply networks to facilitate and coordinate the grid integration of distributed energy resources while enabling the synergies and conflicts between the local distribution networks and the national lev...... and integration of local renewables including solar energy wind geothermal waste heat and biomass is presented.......Energy system integration uses a whole-system approach to optimize the synergies between energy supply networks to facilitate and coordinate the grid integration of distributed energy resources while enabling the synergies and conflicts between the local distribution networks and the national level...... objectives to be understood and optimally coordinated. The latest research on the network coupling technologies analysis of synergies between energy supply networks and optimal use of synergies in network operation is discussed. A diagram on the possible interactions between different energy networks...

Nanosensors-Cellphone Integration for Extended Chemical Sensing Network

Science.gov (United States)

Li, Jing

2011-01-01

This poster is to present the development of a cellphone sensor network for extended chemical sensing. The nanosensors using carbon nanotubes and other nanostructures are used with low power and high sensitivity for chemical detection. The sensing module has been miniaturized to a small size that can plug in or clip on to a smartphone. The chemical information detected by the nanosensors are acquired by a smartphone and transmitted via cellphone 3g or WiFi network to an internet server. The whole integrated sensing system from sensor to cellphone to a cloud will provide an extended chemical sensing network that can cover nation wide and even cover global wide for early warning of a hazardous event.

Development of a Deterministic Optimization Model for Design of an Integrated Utility and Hydrogen Supply Network

International Nuclear Information System (INIS)

Hwangbo, Soonho; Lee, In-Beum; Han, Jeehoon

2014-01-01

Lots of networks are constructed in a large scale industrial complex. Each network meet their demands through production or transportation of materials which are needed to companies in a network. Network directly produces materials for satisfying demands in a company or purchase form outside due to demand uncertainty, financial factor, and so on. Especially utility network and hydrogen network are typical and major networks in a large scale industrial complex. Many studies have been done mainly with focusing on minimizing the total cost or optimizing the network structure. But, few research tries to make an integrated network model by connecting utility network and hydrogen network. In this study, deterministic mixed integer linear programming model is developed for integrating utility network and hydrogen network. Steam Methane Reforming process is necessary for combining two networks. After producing hydrogen from Steam-Methane Reforming process whose raw material is steam vents from utility network, produced hydrogen go into hydrogen network and fulfill own needs. Proposed model can suggest optimized case in integrated network model, optimized blueprint, and calculate optimal total cost. The capability of the proposed model is tested by applying it to Yeosu industrial complex in Korea. Yeosu industrial complex has the one of the biggest petrochemical complex and various papers are based in data of Yeosu industrial complex. From a case study, the integrated network model suggests more optimal conclusions compared with previous results obtained by individually researching utility network and hydrogen network

Monterey Bay National Marine Sanctuary: Sanctuary Integrated Monitoring Network (SIMoN)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Sanctuary Integrated Monitoring Network (SIMoN) is an integrated, long-term program that takes an ecosystem approach to identify and understand changes to the...

Development of virtual private network for JT-60SA CAD integration

International Nuclear Information System (INIS)

Oshima, Takayuki; Fujita, Takaaki; Seki, Masami; Kawashima, Hisato; Hoshino, Katsumichi; Shibanuma, Kiyoshi; Verrecchia, M.; Teuchner, B.

2010-01-01

The CAD models will be exchanged and integrated at Naka for JT-60SA, a common computer network efficiently connected between Naka site and the Garching site is needed to be established. Virtual Private Network (VPN) was introduced with LAN on computer network physically-separated from JAEA intranet area and firewall. In July 2009, a new VPN connection between the Naka and Garching sites has been successfully demonstrated using IPSec-VPN technology with a commercial and cost-effective firewall/router for security. It was found that the introduction of the Wide Area File Service (WAFS) could solve the issue of the data transmission time and enhance the usability of the VPN for design integration in JT-60SA. (author)

Multifractal analysis of complex networks

International Nuclear Information System (INIS)

Wang Dan-Ling; Yu Zu-Guo; Anh V

2012-01-01

Complex networks have recently attracted much attention in diverse areas of science and technology. Many networks such as the WWW and biological networks are known to display spatial heterogeneity which can be characterized by their fractal dimensions. Multifractal analysis is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. In this paper, we introduce a new box-covering algorithm for multifractal analysis of complex networks. This algorithm is used to calculate the generalized fractal dimensions D q of some theoretical networks, namely scale-free networks, small world networks, and random networks, and one kind of real network, namely protein—protein interaction networks of different species. Our numerical results indicate the existence of multifractality in scale-free networks and protein—protein interaction networks, while the multifractal behavior is not clear-cut for small world networks and random networks. The possible variation of D q due to changes in the parameters of the theoretical network models is also discussed. (general)

Integrating network ecology with applied conservation: a synthesis and guide to implementation.

Science.gov (United States)

Kaiser-Bunbury, Christopher N; Blüthgen, Nico

2015-07-10

Ecological networks are a useful tool to study the complexity of biotic interactions at a community level. Advances in the understanding of network patterns encourage the application of a network approach in other disciplines than theoretical ecology, such as biodiversity conservation. So far, however, practical applications have been meagre. Here we present a framework for network analysis to be harnessed to advance conservation management by using plant-pollinator networks and islands as model systems. Conservation practitioners require indicators to monitor and assess management effectiveness and validate overall conservation goals. By distinguishing between two network attributes, the 'diversity' and 'distribution' of interactions, on three hierarchical levels (species, guild/group and network) we identify seven quantitative metrics to describe changes in network patterns that have implications for conservation. Diversity metrics are partner diversity, vulnerability/generality, interaction diversity and interaction evenness, and distribution metrics are the specialization indices d' and [Formula: see text] and modularity. Distribution metrics account for sampling bias and may therefore be suitable indicators to detect human-induced changes to plant-pollinator communities, thus indirectly assessing the structural and functional robustness and integrity of ecosystems. We propose an implementation pathway that outlines the stages that are required to successfully embed a network approach in biodiversity conservation. Most importantly, only if conservation action and study design are aligned by practitioners and ecologists through joint experiments, are the findings of a conservation network approach equally beneficial for advancing adaptive management and ecological network theory. We list potential obstacles to the framework, highlight the shortfall in empirical, mostly experimental, network data and discuss possible solutions. Published by Oxford University

Multi-focus and multi-level techniques for visualization and analysis of networks with thematic data

Science.gov (United States)

Cossalter, Michele; Mengshoel, Ole J.; Selker, Ted

2013-01-01

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when associated with node-link network visualizations. This paper presents an integration of multi-focus and multi-level techniques that enable interactive, multi-step comparisons in node-link networks. We describe NetEx, a visualization tool that enables users to simultaneously explore different parts of a network and its thematic data, such as time series or conditional probability tables. NetEx, implemented as a Cytoscape plug-in, has been applied to the analysis of electrical power networks, Bayesian networks, and the Enron e-mail repository. In this paper we briefly discuss visualization and analysis of the Enron social network, but focus on data from an electrical power network. Specifically, we demonstrate how NetEx supports the analytical task of electrical power system fault diagnosis. Results from a user study with 25 subjects suggest that NetEx enables more accurate isolation of complex faults compared to an especially designed software tool.

Characterization of functional and structural integrity in experimental focal epilepsy: reduced network efficiency coincides with white matter changes.

Directory of Open Access Journals (Sweden)

Willem M Otte

Full Text Available BACKGROUND: Although focal epilepsies are increasingly recognized to affect multiple and remote neural systems, the underlying spatiotemporal pattern and the relationships between recurrent spontaneous seizures, global functional connectivity, and structural integrity remain largely unknown. METHODOLOGY/PRINCIPAL FINDINGS: Here we utilized serial resting-state functional MRI, graph-theoretical analysis of complex brain networks and diffusion tensor imaging to characterize the evolution of global network topology, functional connectivity and structural changes in the interictal brain in relation to focal epilepsy in a rat model. Epileptic networks exhibited a more regular functional topology than controls, indicated by a significant increase in shortest path length and clustering coefficient. Interhemispheric functional connectivity in epileptic brains decreased, while intrahemispheric functional connectivity increased. Widespread reductions of fractional anisotropy were found in white matter regions not restricted to the vicinity of the epileptic focus, including the corpus callosum. CONCLUSIONS/SIGNIFICANCE: Our longitudinal study on the pathogenesis of network dynamics in epileptic brains reveals that, despite the locality of the epileptogenic area, epileptic brains differ in their global network topology, connectivity and structural integrity from healthy brains.

FUZZY NEURAL NETWORK FOR OBJECT IDENTIFICATION ON INTEGRATED CIRCUIT LAYOUTS

Directory of Open Access Journals (Sweden)

A. A. Doudkin

2015-01-01

Full Text Available Fuzzy neural network model based on neocognitron is proposed to identify layout objects on images of topological layers of integrated circuits. Testing of the model on images of real chip layouts was showed a highеr degree of identification of the proposed neural network in comparison to base neocognitron.

Hydrocarbons in Argentina: networks, territories, integration

International Nuclear Information System (INIS)

Carrizo, S.C.

2003-12-01

Argentinean hydrocarbons networks have lived a huge reorganizing the structure, after the State reform in the 90's. Activities deregulation and the privatization of YPF and Gas del Estado forced the sector re-concentration, since then dominated by foreign companies, leaded by Repsol YPF. The hydrocarbons federalization contributed to the weakening and un-capitalization loss of wealth of the State. These changes resulted in an increase of the hydrocarbons production allowing to achieve the self-supply. Nevertheless, the expansion of internal networks has not been large enough to ensure the coverage of new requirements. Besides, several infrastructures have been built up to join external markets. National networks are connected to those of near neighboring countries. This integration is an opportunity for the 'South Cone' countries to enhance their potentials. In the country, hydrocarbons territories undergo the reorganizing the structure effects (unemployment, loss of territorial identity, etc). With many difficulties and very different possibilities, those territories, like Comodoro Rivadavia, Ensenada et and Bahia Blanca, look for their re-invention. (author)

Ecological network analysis: network construction

NARCIS (Netherlands)

Fath, B.D.; Scharler, U.M.; Ulanowicz, R.E.; Hannon, B.

2007-01-01

Ecological network analysis (ENA) is a systems-oriented methodology to analyze within system interactions used to identify holistic properties that are otherwise not evident from the direct observations. Like any analysis technique, the accuracy of the results is as good as the data available, but

Time series analysis of temporal networks

Science.gov (United States)

Sikdar, Sandipan; Ganguly, Niloy; Mukherjee, Animesh

2016-01-01

A common but an important feature of all real-world networks is that they are temporal in nature, i.e., the network structure changes over time. Due to this dynamic nature, it becomes difficult to propose suitable growth models that can explain the various important characteristic properties of these networks. In fact, in many application oriented studies only knowing these properties is sufficient. For instance, if one wishes to launch a targeted attack on a network, this can be done even without the knowledge of the full network structure; rather an estimate of some of the properties is sufficient enough to launch the attack. We, in this paper show that even if the network structure at a future time point is not available one can still manage to estimate its properties. We propose a novel method to map a temporal network to a set of time series instances, analyze them and using a standard forecast model of time series, try to predict the properties of a temporal network at a later time instance. To our aim, we consider eight properties such as number of active nodes, average degree, clustering coefficient etc. and apply our prediction framework on them. We mainly focus on the temporal network of human face-to-face contacts and observe that it represents a stochastic process with memory that can be modeled as Auto-Regressive-Integrated-Moving-Average (ARIMA). We use cross validation techniques to find the percentage accuracy of our predictions. An important observation is that the frequency domain properties of the time series obtained from spectrogram analysis could be used to refine the prediction framework by identifying beforehand the cases where the error in prediction is likely to be high. This leads to an improvement of 7.96% (for error level ≤20%) in prediction accuracy on an average across all datasets. As an application we show how such prediction scheme can be used to launch targeted attacks on temporal networks. Contribution to the Topical Issue

Integration of biological networks and gene expression data using Cytoscape

DEFF Research Database (Denmark)

Cline, M.S.; Smoot, M.; Cerami, E.

2007-01-01

of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules......Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context...... and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape....

Complex Behavior in an Integrate-and-Fire Neuron Model Based on Small World Networks

International Nuclear Information System (INIS)

Lin Min; Chen Tianlun

2005-01-01

Based on our previously pulse-coupled integrate-and-fire neuron model in small world networks, we investigate the complex behavior of electroencephalographic (EEG)-like activities produced by such a model. We find EEG-like activities have obvious chaotic characteristics. We also analyze the complex behaviors of EEG-like signals, such as spectral analysis, reconstruction of the phase space, the correlation dimension, and so on.

The network perspective: an integration of attachment and family systems theories.

Science.gov (United States)

Kozlowska, Kasia; Hanney, Lesley

2002-01-01

In this article we discuss the network paradigm as a useful base from which to integrate attachment and family systems theories. The network perspective refers to the application of general systems theory to living systems, and provides a framework that conceptualizes the dyadic and family systems as simultaneously distinct and interconnected. Network thinking requires that the clinician holds multiple perspectives in mind, considers each system level as both a part and a whole, and shifts the focus of attention between levels as required. Key epistemological issues that have hindered the integration of the theories are discussed. These include inconsistencies within attachment theory itself and confusion surrounding the theoretical conceptualizations of the relationship between attachment and family systems theories. Detailed information about attachment categories is provided using the Dynamic Maturational model. Case vignettes illustrating work with young children and their families explore the clinical implications of integrating attachment data into family therapy practice.

Synaptic integration of transplanted interneuron progenitor cells into native cortical networks.

Science.gov (United States)

Howard, MacKenzie A; Baraban, Scott C

2016-08-01

Interneuron-based cell transplantation is a powerful method to modify network function in a variety of neurological disorders, including epilepsy. Whether new interneurons integrate into native neural networks in a subtype-specific manner is not well understood, and the therapeutic mechanisms underlying interneuron-based cell therapy, including the role of synaptic inhibition, are debated. In this study, we tested subtype-specific integration of transplanted interneurons using acute cortical brain slices and visualized patch-clamp recordings to measure excitatory synaptic inputs, intrinsic properties, and inhibitory synaptic outputs. Fluorescently labeled progenitor cells from the embryonic medial ganglionic eminence (MGE) were used for transplantation. At 5 wk after transplantation, MGE-derived parvalbumin-positive (PV+) interneurons received excitatory synaptic inputs, exhibited mature interneuron firing properties, and made functional synaptic inhibitory connections to native pyramidal cells that were comparable to those of native PV+ interneurons. These findings demonstrate that MGE-derived PV+ interneurons functionally integrate into subtype-appropriate physiological niches within host networks following transplantation. Copyright © 2016 the American Physiological Society.

Proposition of a modeling and an analysis methodology of integrated reverse logistics chain in the direct chain

Energy Technology Data Exchange (ETDEWEB)

Mimouni, F.; Abouabdellah, A.

2016-07-01

Propose a modeling and analysis methodology based on the combination of Bayesian networks and Petri networks of the reverse logistics integrated the direct supply chain. Network modeling by combining Petri and Bayesian network. Modeling with Bayesian network complimented with Petri network to break the cycle problem in the Bayesian network. Demands are independent from returns. Model can only be used on nonperishable products. Legislation aspects: Recycling laws; Protection of environment; Client satisfaction via after sale service. Bayesian network with a cycle combined with the Petri Network. (Author)

Survivable integrated grooming in multi-granularity optical networks

Science.gov (United States)

Wu, Jingjing; Guo, Lei; Wei, Xuetao; Liu, Yejun

2012-05-01

Survivability is an important issue to ensure the service continuity in optical network. At the same time, with the granularity of traffic demands ranging from sub-wavelength-level to wavelength-level, traffic demands need to be aggregated and carried over the network in order to utilize resources effectively. Therefore, multi-granularity grooming is proposed to save the cost and reduce the number of switching ports in Optical-Cross Connects (OXCs). However, current works mostly addressed the survivable wavelength or waveband grooming. Therefore, in this paper, we propose three heuristic algorithms called Multi-granularity Dedicated Protection Grooming (MDPG), Multi-granularity Shared Protection Grooming (MSPG) and Multi-granularity Mixed Protection Grooming (MMPG), respectively. All of them are performed based on the Survivable Multi-granularity Integrated Auxiliary Graph (SMIAG) that includes one Wavelength Integrated Auxiliary Graph (WIAG) for wavelength protection and one waveBand Integrated Auxiliary Graph (BIAG) for waveband protection. Numerical results show that MMPG has the lowest average port-cost, the best resource utilization ratio and the lowest blocking probability among these three algorithms. Compared with MDPG, MSPG has lower average port-cost, better resource utilization ratio and lower blocking probability.

Penalized differential pathway analysis of integrative oncogenomics studies.

Science.gov (United States)

van Wieringen, Wessel N; van de Wiel, Mark A

2014-04-01

Through integration of genomic data from multiple sources, we may obtain a more accurate and complete picture of the molecular mechanisms underlying tumorigenesis. We discuss the integration of DNA copy number and mRNA gene expression data from an observational integrative genomics study involving cancer patients. The two molecular levels involved are linked through the central dogma of molecular biology. DNA copy number aberrations abound in the cancer cell. Here we investigate how these aberrations affect gene expression levels within a pathway using observational integrative genomics data of cancer patients. In particular, we aim to identify differential edges between regulatory networks of two groups involving these molecular levels. Motivated by the rate equations, the regulatory mechanism between DNA copy number aberrations and gene expression levels within a pathway is modeled by a simultaneous-equations model, for the one- and two-group case. The latter facilitates the identification of differential interactions between the two groups. Model parameters are estimated by penalized least squares using the lasso (L1) penalty to obtain a sparse pathway topology. Simulations show that the inclusion of DNA copy number data benefits the discovery of gene-gene interactions. In addition, the simulations reveal that cis-effects tend to be over-estimated in a univariate (single gene) analysis. In the application to real data from integrative oncogenomic studies we show that inclusion of prior information on the regulatory network architecture benefits the reproducibility of all edges. Furthermore, analyses of the TP53 and TGFb signaling pathways between ER+ and ER- samples from an integrative genomics breast cancer study identify reproducible differential regulatory patterns that corroborate with existing literature.

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network.

Science.gov (United States)

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection.

Tensions in R&D networks : Implications for knowledge search and integration

NARCIS (Netherlands)

Ritala, Paavo; Huizingh, Eelko; Almpanopoulou, Argyro; Wijbenga, Paul

R&D Networks comprise different actors with various goals and motivations. Thus, such networks are filled with tensions that emerge from simultaneously existing, competing or contradictory organizing elements and demands. In this study, we examine the knowledge search and integration behaviour of

Implementation of Integrated Service Networks under the Quebec Mental Health Reform: Facilitators and Barriers associated with Different Territorial Profiles.

Science.gov (United States)

Fleury, Marie-Josée; Grenier, Guy; Vallée, Catherine; Aubé, Denise; Farand, Lambert

2017-03-10

This study evaluates implementation of the Quebec Mental Health Reform (2005-2015), which promoted the development of integrated service networks, in 11 local service networks organized into four territorial groups according to socio-demographic characteristics and mental health services offered. Data were collected from documents concerning networks; structured questionnaires completed by 90 managers and by 16 respondent-psychiatrists; and semi-structured interviews with 102 network stakeholders. Factors associated with implementation and integration were organized according to: 1) reform characteristics; 2) implementation context; 3) organizational characteristics; and 4) integration strategies. While local networks were in a process of development and expansion, none were fully integrated at the time of the study. Facilitators and barriers to implementation and integration were primarily associated with organizational characteristics. Integration was best achieved in larger networks including a general hospital with a psychiatric department, followed by networks with a psychiatric hospital. Formalized integration strategies such as service agreements, liaison officers, and joint training reduced some barriers to implementation in networks experiencing less favourable conditions. Strategies for the implementation of healthcare reform and integrated service networks should include sustained support and training in best-practices, adequate performance indicators and resources, formalized integration strategies to improve network coordination and suitable initiatives to promote staff retention.

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

Science.gov (United States)

Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

2012-01-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks.

Science.gov (United States)

Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A; Kellis, Manolis

2012-07-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein-protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level.

Integrated Meteorological Observation Network in Castile-León (Spain)

Science.gov (United States)

Merino, A.; Guerrero-Higueras, A. M.; Ortiz de Galisteo, J. P.; López, L.; García-Ortega, E.; Nafría, D. A.; Sánchez, J. L.

2012-04-01

In the region of Castile-Leon, in the northwest of Spain, the study of weather risks is extremely complex because of the topography, the large land area of the region and the variety of climatic features involved. Therefore, as far as the calibration and validation of the necessary tools for the identification and nowcasting of these risks are concerned, one of the most important difficulties is the lack of observed data. The same problem arises, for example, in the analysis of particularly relevant case studies. It was hence deemed necessary to create an INTEGRATED METEOROLOGICAL OBSERVATION NETWORK FOR CASTILE-LEON. The aim of this network is to integrate within one single platform all the ground truth data available. These data enable us to detect a number of weather risks in real time. The various data sources should include the networks from the weather stations run by different public institutions - national and regional ones (AEMET, Junta de Castilla y León, Universities, etc.) -, as well as the stations run by voluntary observers. The platform will contain real or cuasi-real time data from the ground weather stations, but it will also have applications to enable voluntary observers to indicate the presence or absence of certain meteors (snow, hail) or even provide detailed information about them (hailstone size, graupel, etc.). The data managed by this network have a high scientific potential, as they may be used for a number of different purposes: calibration and validation of remote sensing tools, assimilation of observation data from numerical models, study of extreme weather events, etc. An additional aim of the network is the drawing of maps of weather risks in real time. These maps are of great importance for the people involved in risk management in each region, as well as for the general public. Finally, one of the first applications developed has been the creation of observation maps in real time. These applications have been constructed using NCL

Structural analysis of health-relevant policy-making information exchange networks in Canada.

Science.gov (United States)

Contandriopoulos, Damien; Benoît, François; Bryant-Lukosius, Denise; Carrier, Annie; Carter, Nancy; Deber, Raisa; Duhoux, Arnaud; Greenhalgh, Trisha; Larouche, Catherine; Leclerc, Bernard-Simon; Levy, Adrian; Martin-Misener, Ruth; Maximova, Katerina; McGrail, Kimberlyn; Nykiforuk, Candace; Roos, Noralou; Schwartz, Robert; Valente, Thomas W; Wong, Sabrina; Lindquist, Evert; Pullen, Carolyn; Lardeux, Anne; Perroux, Melanie

2017-09-20

Health systems worldwide struggle to identify, adopt, and implement in a timely and system-wide manner the best-evidence-informed-policy-level practices. Yet, there is still only limited evidence about individual and institutional best practices for fostering the use of scientific evidence in policy-making processes The present project is the first national-level attempt to (1) map and structurally analyze-quantitatively-health-relevant policy-making networks that connect evidence production, synthesis, interpretation, and use; (2) qualitatively investigate the interaction patterns of a subsample of actors with high centrality metrics within these networks to develop an in-depth understanding of evidence circulation processes; and (3) combine these findings in order to assess a policy network's "absorptive capacity" regarding scientific evidence and integrate them into a conceptually sound and empirically grounded framework. The project is divided into two research components. The first component is based on quantitative analysis of ties (relationships) that link nodes (participants) in a network. Network data will be collected through a multi-step snowball sampling strategy. Data will be analyzed structurally using social network mapping and analysis methods. The second component is based on qualitative interviews with a subsample of the Web survey participants having central, bridging, or atypical positions in the network. Interviews will focus on the process through which evidence circulates and enters practice. Results from both components will then be integrated through an assessment of the network's and subnetwork's effectiveness in identifying, capturing, interpreting, sharing, reframing, and recodifying scientific evidence in policy-making processes. Knowledge developed from this project has the potential both to strengthen the scientific understanding of how policy-level knowledge transfer and exchange functions and to provide significantly improved advice

Control strategies for power distribution networks with electric vehicles integration

DEFF Research Database (Denmark)

Hu, Junjie

of electrical energy. A smart grid can also be dened as an electricity network that can intelligently integrate the actions of all users connected to it - generators, consumers and those that do both - in order to eciently deliver sustainable, economic and secure electricity supplies. This thesis focuses...... of the ii market. To build a complete solution for integration of EVs into the distribution network, a price coordinated hierarchical scheduling system is proposed which can well characterize the involved actors in the smart grid. With this system, we demonstrate that it is possible to schedule the charging......Demand side resources, like electric vehicles (EVs), can become integral parts of a smart grids because instead of just consuming power they are capable of providing valuable services to power systems. EVs can be used to balance the intermittent renewable energy resources such as wind and solar...

ICan: an integrated co-alteration network to identify ovarian cancer-related genes.

Science.gov (United States)

Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

2015-01-01

Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data.

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.

Reduced integration and improved segregation of functional brain networks in Alzheimer's disease.

Science.gov (United States)

Kabbara, A; Eid, H; El Falou, W; Khalil, M; Wendling, F; Hassan, M

2018-04-01

Emerging evidence shows that cognitive deficits in Alzheimer's disease (AD) are associated with disruptions in brain functional connectivity. Thus, the identification of alterations in AD functional networks has become a topic of increasing interest. However, to what extent AD induces disruption of the balance of local and global information processing in the human brain remains elusive. The main objective of this study is to explore the dynamic topological changes of AD networks in terms of brain network segregation and integration. We used electroencephalography (EEG) data recorded from 20 participants (10 AD patients and 10 healthy controls) during resting state. Functional brain networks were reconstructed using EEG source connectivity computed in different frequency bands. Graph theoretical analyses were performed assess differences between both groups. Results revealed that AD networks, compared to networks of age-matched healthy controls, are characterized by lower global information processing (integration) and higher local information processing (segregation). Results showed also significant correlation between the alterations in the AD patients' functional brain networks and their cognitive scores. These findings may contribute to the development of EEG network-based test that could strengthen results obtained from currently-used neurophysiological tests in neurodegenerative diseases.

Probabilistic Inference of Biological Networks via Data Integration

Directory of Open Access Journals (Sweden)

Mark F. Rogers

2015-01-01

Full Text Available There is significant interest in inferring the structure of subcellular networks of interaction. Here we consider supervised interactive network inference in which a reference set of known network links and nonlinks is used to train a classifier for predicting new links. Many types of data are relevant to inferring functional links between genes, motivating the use of data integration. We use pairwise kernels to predict novel links, along with multiple kernel learning to integrate distinct sources of data into a decision function. We evaluate various pairwise kernels to establish which are most informative and compare individual kernel accuracies with accuracies for weighted combinations. By associating a probability measure with classifier predictions, we enable cautious classification, which can increase accuracy by restricting predictions to high-confidence instances, and data cleaning that can mitigate the influence of mislabeled training instances. Although one pairwise kernel (the tensor product pairwise kernel appears to work best, different kernels may contribute complimentary information about interactions: experiments in S. cerevisiae (yeast reveal that a weighted combination of pairwise kernels applied to different types of data yields the highest predictive accuracy. Combined with cautious classification and data cleaning, we can achieve predictive accuracies of up to 99.6%.

Integrating atomistic molecular dynamics simulations, experiments and network analysis to study protein dynamics: strength in unity

Directory of Open Access Journals (Sweden)

Elena ePapaleo

2015-05-01

Full Text Available In the last years, we have been observing remarkable improvements in the field of protein dynamics. Indeed, we can now study protein dynamics in atomistic details over several timescales with a rich portfolio of experimental and computational techniques. On one side, this provides us with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome their own limitations. Moreover, now that we have the means to study protein dynamics in great details, we need new tools to understand the information embedded in the protein ensembles and in their dynamic signature. With this aim in mind, we should enrich the current tools for analysis of biomolecular simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations.

Network Analysis, Architecture, and Design

CERN Document Server

McCabe, James D

2007-01-01

Traditionally, networking has had little or no basis in analysis or architectural development, with designers relying on technologies they are most familiar with or being influenced by vendors or consultants. However, the landscape of networking has changed so that network services have now become one of the most important factors to the success of many third generation networks. It has become an important feature of the designer's job to define the problems that exist in his network, choose and analyze several optimization parameters during the analysis process, and then prioritize and evalua

Social networking in nursing education: integrative literature review.

Science.gov (United States)

Kakushi, Luciana Emi; Évora, Yolanda Dora Martinez

2016-01-01

to identify the use of social networking in nursing education. integrative literature review in the databases: LILACS, IBECS, Cochrane, BDENF, SciELO, CINAHL, Scopus, PubMed, CAPES Periodicals Portal and Web of Science, using the descriptors: social networking and nursing education and the keywords: social networking sites and nursing education, carried out in April 2015. of the 489 articles found, only 14 met the inclusion and exclusion criteria. Most studies were published after 2013 (57%), originating from the United States and United Kingdom (77.8%). It was observed the use of social networking among nursing students, postgraduate students, mentors and nurses, in undergraduate programmes, hybrid education (blended-learning) and in interprofessional education. The social networking sites used in the teaching and learning process were Facebook (42.8%), Ning (28.5%), Twitter (21.4%) and MySpace (7.1%), by means of audios, videos, quizzes, animations, forums, guidance, support, discussions and research group. few experiences of the use of social networking in nursing education were found and their contributions show the numerous benefits and difficulties faced, providing resourses for the improvement and revaluation of their use in the teaching and learning process.

Social networking in nursing education: integrative literature review

Directory of Open Access Journals (Sweden)

Luciana Emi Kakushi

Full Text Available Abstract Objective: to identify the use of social networking in nursing education. Method: integrative literature review in the databases: LILACS, IBECS, Cochrane, BDENF, SciELO, CINAHL, Scopus, PubMed, CAPES Periodicals Portal and Web of Science, using the descriptors: social networking and nursing education and the keywords: social networking sites and nursing education, carried out in April 2015. Results: of the 489 articles found, only 14 met the inclusion and exclusion criteria. Most studies were published after 2013 (57%, originating from the United States and United Kingdom (77.8%. It was observed the use of social networking among nursing students, postgraduate students, mentors and nurses, in undergraduate programmes, hybrid education (blended-learning and in interprofessional education. The social networking sites used in the teaching and learning process were Facebook (42.8%, Ning (28.5%, Twitter (21.4% and MySpace (7.1%, by means of audios, videos, quizzes, animations, forums, guidance, support, discussions and research group. Conclusion: few experiences of the use of social networking in nursing education were found and their contributions show the numerous benefits and difficulties faced, providing resourses for the improvement and revaluation of their use in the teaching and learning process.

Functional brain networks contributing to the Parieto-Frontal Integration Theory of Intelligence.

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Vakhtin, Andrei A; Ryman, Sephira G; Flores, Ranee A; Jung, Rex E

2014-12-01

The refinement of localization of intelligence in the human brain is converging onto a distributed network that broadly conforms to the Parieto-Frontal Integration Theory (P-FIT). While this theory has received support in the neuroimaging literature, no functional magnetic resonance imaging study to date has conducted a whole-brain network-wise examination of the changes during engagement in tasks that are reliable measures of general intelligence (e.g., Raven's Progressive Matrices Test; RPM). Seventy-nine healthy subjects were scanned while solving RPM problems and during rest. Functional networks were extracted from the RPM and resting state data using Independent Component Analysis. Twenty-nine networks were identified, 26 of which were detected in both conditions. Fourteen networks were significantly correlated with the RPM task. The networks' spatial maps and functional connectivity measures at 3 frequency levels (low, medium, & high) were compared between the RPM and rest conditions. The regions involved in the networks that were found to be task related were consistent with the P-FIT, localizing to the bilateral medial frontal and parietal regions, right superior frontal lobule, and the right cingulate gyrus. Functional connectivity in multiple component pairs was differentially affected across all frequency levels during the RPM task. Our findings demonstrate that functional brain networks are more stable than previously thought, and maintain their general features across resting state and engagement in a complex cognitive task. The described spatial and functional connectivity alterations that such components undergo during fluid reasoning provide a network-wise framework of the P-FIT that can be valuable for further, network based, neuroimaging inquiries regarding the neural underpinnings of intelligence. Published by Elsevier Inc.

Integrated workflow for characterizing and modeling fracture network in unconventional reservoirs using microseismic data

Science.gov (United States)

Ayatollahy Tafti, Tayeb

We develop a new method for integrating information and data from different sources. We also construct a comprehensive workflow for characterizing and modeling a fracture network in unconventional reservoirs, using microseismic data. The methodology is based on combination of several mathematical and artificial intelligent techniques, including geostatistics, fractal analysis, fuzzy logic, and neural networks. The study contributes to scholarly knowledge base on the characterization and modeling fractured reservoirs in several ways; including a versatile workflow with a novel objective functions. Some the characteristics of the methods are listed below: 1. The new method is an effective fracture characterization procedure estimates different fracture properties. Unlike the existing methods, the new approach is not dependent on the location of events. It is able to integrate all multi-scaled and diverse fracture information from different methodologies. 2. It offers an improved procedure to create compressional and shear velocity models as a preamble for delineating anomalies and map structures of interest and to correlate velocity anomalies with fracture swarms and other reservoir properties of interest. 3. It offers an effective way to obtain the fractal dimension of microseismic events and identify the pattern complexity, connectivity, and mechanism of the created fracture network. 4. It offers an innovative method for monitoring the fracture movement in different stages of stimulation that can be used to optimize the process. 5. Our newly developed MDFN approach allows to create a discrete fracture network model using only microseismic data with potential cost reduction. It also imposes fractal dimension as a constraint on other fracture modeling approaches, which increases the visual similarity between the modeled networks and the real network over the simulated volume.

Spontaneous brain network activity: Analysis of its temporal complexity

Directory of Open Access Journals (Sweden)

Mangor Pedersen

2017-06-01

Full Text Available The brain operates in a complex way. The temporal complexity underlying macroscopic and spontaneous brain network activity is still to be understood. In this study, we explored the brain’s complexity by combining functional connectivity, graph theory, and entropy analyses in 25 healthy people using task-free functional magnetic resonance imaging. We calculated the pairwise instantaneous phase synchrony between 8,192 brain nodes for a total of 200 time points. This resulted in graphs for which time series of clustering coefficients (the “cliquiness” of a node and participation coefficients (the between-module connectivity of a node were estimated. For these two network metrics, sample entropy was calculated. The procedure produced a number of results: (1 Entropy is higher for the participation coefficient than for the clustering coefficient. (2 The average clustering coefficient is negatively related to its associated entropy, whereas the average participation coefficient is positively related to its associated entropy. (3 The level of entropy is network-specific to the participation coefficient, but not to the clustering coefficient. High entropy for the participation coefficient was observed in the default-mode, visual, and motor networks. These results were further validated using an independent replication dataset. Our work confirms that brain networks are temporally complex. Entropy is a good candidate metric to explore temporal network alterations in diseases with paroxysmal brain disruptions, including schizophrenia and epilepsy. In recent years, connectomics has provided significant insights into the topological complexity of brain networks. However, the temporal complexity of brain networks still remains somewhat poorly understood. In this study we used entropy analysis to demonstrate that the properties of network segregation (the clustering coefficient and integration (the participation coefficient are temporally complex

On the area spectral efficiency improvement of heterogeneous network by exploiting the integration of macro-femto cellular networks

KAUST Repository

Shakir, Muhammad; Alouini, Mohamed-Slim

2012-01-01

. In this paper, we consider a Heterogeneous network where we complement the macrocell network with low-power low-cost user deployed nodes, such as femtocell base stations to increase the mean achievable capacity of the system. In this context, we integrate macro

Analysis of Semantic Networks using Complex Networks Concepts

DEFF Research Database (Denmark)

Ortiz-Arroyo, Daniel

2013-01-01

In this paper we perform a preliminary analysis of semantic networks to determine the most important terms that could be used to optimize a summarization task. In our experiments, we measure how the properties of a semantic network change, when the terms in the network are removed. Our preliminar...

Issues for the integration of satellite and terrestrial cellular networks for mobile communications

Science.gov (United States)

Delre, Enrico; Mistretta, Ignazio; Dellipriscoli, Francesco; Settimo, Franco

1991-01-01

Satellite and terrestrial cellular systems naturally complement each other for land mobile communications, even though present systems have been developed independently. The main advantages of the integrated system are a faster wide area coverage, a better management of overloading traffic conditions, an extension to geographical areas not covered by the terrestrial network and, in perspective, the provision of only one integrated system for all mobile communications (land, aeronautical, and maritime). To achieve these goals, as far as possible the same protocols of the terrestrial network should be used also for the satellite network. Discussed here are the main issues arising from the requirements of the main integrated system. Some results are illustrated, and possible future improvements due to technical solutions are presented.

ISINA: INTEGRAL Source Identification Network Algorithm

Science.gov (United States)

Scaringi, S.; Bird, A. J.; Clark, D. J.; Dean, A. J.; Hill, A. B.; McBride, V. A.; Shaw, S. E.

2008-11-01

We give an overview of ISINA: INTEGRAL Source Identification Network Algorithm. This machine learning algorithm, using random forests, is applied to the IBIS/ISGRI data set in order to ease the production of unbiased future soft gamma-ray source catalogues. First, we introduce the data set and the problems encountered when dealing with images obtained using the coded mask technique. The initial step of source candidate searching is introduced and an initial candidate list is created. A description of the feature extraction on the initial candidate list is then performed together with feature merging for these candidates. Three training and testing sets are created in order to deal with the diverse time-scales encountered when dealing with the gamma-ray sky. Three independent random forests are built: one dealing with faint persistent source recognition, one dealing with strong persistent sources and a final one dealing with transients. For the latter, a new transient detection technique is introduced and described: the transient matrix. Finally the performance of the network is assessed and discussed using the testing set and some illustrative source examples. Based on observations with INTEGRAL, an ESA project with instruments and science data centre funded by ESA member states (especially the PI countries: Denmark, France, Germany, Italy, Spain), Czech Republic and Poland, and the participation of Russia and the USA. E-mail: simo@astro.soton.ac.uk

NETWORK CULTURE - INTEGRAL PART OF NEW VALUES OF CIVIL SOCIETY

OpenAIRE

Vyacheslav Vladimirovich Sukhanov

2014-01-01

New technologies not only improve working conditions or communication, they are also bringing new values to  the society. This article discusses the concept of «network culture», which is now perceived by society as an integral part of values that can only exist in a civil society. We can research ( find)   this kind of society in modern time period in Russia. The article analyzes the meaning of communication, how to use it, development processes in network media.  Nowadays network culture an...

VitisNet: "Omics" integration through grapevine molecular networks.

Directory of Open Access Journals (Sweden)

Jérôme Grimplet

Full Text Available BACKGROUND: Genomic data release for the grapevine has increased exponentially in the last five years. The Vitis vinifera genome has been sequenced and Vitis EST, transcriptomic, proteomic, and metabolomic tools and data sets continue to be developed. The next critical challenge is to provide biological meaning to this tremendous amount of data by annotating genes and integrating them within their biological context. We have developed and validated a system of Grapevine Molecular Networks (VitisNet. METHODOLOGY/PRINCIPAL FINDINGS: The sequences from the Vitis vinifera (cv. Pinot Noir PN40024 genome sequencing project and ESTs from the Vitis genus have been paired and the 39,424 resulting unique sequences have been manually annotated. Among these, 13,145 genes have been assigned to 219 networks. The pathway sets include 88 "Metabolic", 15 "Genetic Information Processing", 12 "Environmental Information Processing", 3 "Cellular Processes", 21 "Transport", and 80 "Transcription Factors". The quantitative data is loaded onto molecular networks, allowing the simultaneous visualization of changes in the transcriptome, proteome, and metabolome for a given experiment. CONCLUSIONS/SIGNIFICANCE: VitisNet uses manually annotated networks in SBML or XML format, enabling the integration of large datasets, streamlining biological functional processing, and improving the understanding of dynamic processes in systems biology experiments. VitisNet is grounded in the Vitis vinifera genome (currently at 8x coverage and can be readily updated with subsequent updates of the genome or biochemical discoveries. The molecular network files can be dynamically searched by pathway name or individual genes, proteins, or metabolites through the MetNet Pathway database and web-portal at http://metnet3.vrac.iastate.edu/. All VitisNet files including the manual annotation of the grape genome encompassing pathway names, individual genes, their genome identifier, and chromosome

Hybrid modeling and empirical analysis of automobile supply chain network

Science.gov (United States)

Sun, Jun-yan; Tang, Jian-ming; Fu, Wei-ping; Wu, Bing-ying

2017-05-01

Based on the connection mechanism of nodes which automatically select upstream and downstream agents, a simulation model for dynamic evolutionary process of consumer-driven automobile supply chain is established by integrating ABM and discrete modeling in the GIS-based map. Firstly, the rationality is proved by analyzing the consistency of sales and changes in various agent parameters between the simulation model and a real automobile supply chain. Second, through complex network theory, hierarchical structures of the model and relationships of networks at different levels are analyzed to calculate various characteristic parameters such as mean distance, mean clustering coefficients, and degree distributions. By doing so, it verifies that the model is a typical scale-free network and small-world network. Finally, the motion law of this model is analyzed from the perspective of complex self-adaptive systems. The chaotic state of the simulation system is verified, which suggests that this system has typical nonlinear characteristics. This model not only macroscopically illustrates the dynamic evolution of complex networks of automobile supply chain but also microcosmically reflects the business process of each agent. Moreover, the model construction and simulation of the system by means of combining CAS theory and complex networks supplies a novel method for supply chain analysis, as well as theory bases and experience for supply chain analysis of auto companies.

Partnership effectiveness in primary community care networks: A national empirical analysis of partners' coordination infrastructure designs.

Science.gov (United States)

Lin, Blossom Yen-Ju; Lin, Yung-Kai; Lin, Cheng-Chieh

2010-01-01

Previous empirical and managerial studies have ignored the effectiveness of integrated health networks. It has been argued that the varying definitions and strategic imperatives of integrated organizations may have complicated the assessment of the outcomes/performance of varying models, particularly when their market structures and contexts differed. This study aimed to empirically verify a theoretical perspective on the coordination infrastructure designs and the effectiveness of the primary community care networks (PCCNs) formed and funded by the Bureau of National Health Insurance since March 2003. The PCCNs present a model to replace the traditional fragmented providers in Taiwan's health care. The study used a cross-sectional mailed survey designed to ascertain partnership coordination infrastructure and integration of governance, clinical care, bonding, finances, and information. The outcome indicators were PCCNs' perceived performance and willingness to remain within the network. Structural equation modeling examined the causal relationships, controlling for organizational and environmental factors. Primary data collection occurred from February through December 2005, via structured questionnaires sent to 172 PCCNs. Using the individual PCCN as the unit of analysis, the results found that a network's efforts regarding coordination infrastructures were positively related to the PCCN's perceived performance and willingness to remain within the network. In addition, PCCNs practicing in rural areas and in areas with higher density of medical resources had better perceived effectiveness and willingness to cooperate in the network.Practical Implication: The lack of both an operational definition and an information about system-wide integration may have obstructed understanding of integrated health networks' organizational dynamics. This study empirically examined individual PCCNs and offers new insights on how to improve networks' organizational design and

Neural network integration during the perception of in-group and out-group members.

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Greven, Inez M; Ramsey, Richard

2017-11-01

Group biases guide social interactions by promoting in-group favouritism, but the neural mechanisms underpinning group biases remain unclear. While neuroscience research has shown that distributed brain circuits are associated with seeing in-group and out-group members as "us" and "them", it is less clear how these networks exchange signals. This fMRI study uses functional connectivity analyses to investigate the contribution of functional integration to group bias modulation of person perception. Participants were assigned to an arbitrary group and during scanning they observed bodies of in-group or out-group members that cued the recall of positive or negative social knowledge. The results showed that functional coupling between perceptual and cognitive neural networks is tuned to particular combinations of group membership and social knowledge valence. Specifically, coupling between body perception and theory-of-mind networks is biased towards seeing a person that had previously been paired with information consistent with group bias (positive for in-group and negative for out-group). This demonstrates how brain regions associated with visual analysis of others and belief reasoning exchange and integrate signals when evaluating in-group and out-group members. The results update models of person perception by showing how and when interplay occurs between perceptual and extended systems when developing a representation of another person. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Integrated Optimization of Service-Oriented Train Plan and Schedule on Intercity Rail Network with Varying Demand

Directory of Open Access Journals (Sweden)

Wenliang Zhou

2015-01-01

Full Text Available For a better service level of a train operating plan, we propose an integrated optimization method of train planning and train scheduling, which generally are optimized, respectively. Based on the cost analysis of both passengers travelling and enterprises operation, and the constraint analysis of trains operation, we construct a multiobjective function and build an integrated optimization model with the aim of reducing both passenger travel costs and enterprise operating costs. Then, a solving algorithm is established based on the simulated annealing algorithm. Finally, using as an example the Changzhutan intercity rail network, as an example we analyze the optimized results and the influence of the model parameters on the results.

Intelligent Networks Data Fusion Web-based Services for Ad-hoc Integrated WSNs-RFID

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Falah Alshahrany

2016-01-01

Full Text Available The use of variety of data fusion tools and techniques for big data processing poses the problem of the data and information integration called data fusion having objectives which can differ from one application to another. The design of network data fusion systems aimed at meeting these objectives, need to take into account of the necessary synergy that can result from distributed data processing within the data networks and data centres, involving increased computation and communication. This papers reports on how this processing distribution is functionally structured as configurable integrated web-based support services, in the context of an ad-hoc wireless sensor network used for sensing and tracking, in the context of distributed detection based on complete observations to support real rime decision making. The interrelated functional and hardware RFID-WSN integration is an essential aspect of the data fusion framework that focuses on multi-sensor collaboration as an innovative approach to extend the heterogeneity of the devices and sensor nodes of ad-hoc networks generating a huge amount of heterogeneous soft and hard raw data. The deployment and configuration of these networks require data fusion processing that includes network and service management and enhances the performance and reliability of networks data fusion support systems providing intelligent capabilities for real-time control access and fire detection.

A Systems Approach to Refine Disease Taxonomy by Integrating Phenotypic and Molecular Networks

Directory of Open Access Journals (Sweden)

Xuezhong Zhou

2018-05-01

Full Text Available The International Classification of Diseases (ICD relies on clinical features and lags behind the current understanding of the molecular specificity of disease pathobiology, necessitating approaches that incorporate growing biomedical data for classifying diseases to meet the needs of precision medicine. Our analysis revealed that the heterogeneous molecular diversity of disease chapters and the blurred boundary between disease categories in ICD should be further investigated. Here, we propose a new classification of diseases (NCD by developing an algorithm that predicts the additional categories of a disease by integrating multiple networks consisting of disease phenotypes and their molecular profiles. With statistical validations from phenotype-genotype associations and interactome networks, we demonstrate that NCD improves disease specificity owing to its overlapping categories and polyhierarchical structure. Furthermore, NCD captures the molecular diversity of diseases and defines clearer boundaries in terms of both phenotypic similarity and molecular associations, establishing a rational strategy to reform disease taxonomy. Keywords: Disease taxonomy, Network medicine, Disease phenotypes, Molecular profiles, Precision medicine

Training and operation of an integrated neuromorphic network based on metal-oxide memristors

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Prezioso, M.; Merrikh-Bayat, F.; Hoskins, B. D.; Adam, G. C.; Likharev, K. K.; Strukov, D. B.

2015-05-01

Despite much progress in semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex, with its approximately 1014 synapses, makes the hardware implementation of neuromorphic networks with a comparable number of devices exceptionally challenging. To provide comparable complexity while operating much faster and with manageable power dissipation, networks based on circuits combining complementary metal-oxide-semiconductors (CMOSs) and adjustable two-terminal resistive devices (memristors) have been developed. In such circuits, the usual CMOS stack is augmented with one or several crossbar layers, with memristors at each crosspoint. There have recently been notable improvements in the fabrication of such memristive crossbars and their integration with CMOS circuits, including first demonstrations of their vertical integration. Separately, discrete memristors have been used as artificial synapses in neuromorphic networks. Very recently, such experiments have been extended to crossbar arrays of phase-change memristive devices. The adjustment of such devices, however, requires an additional transistor at each crosspoint, and hence these devices are much harder to scale than metal-oxide memristors, whose nonlinear current-voltage curves enable transistor-free operation. Here we report the experimental implementation of transistor-free metal-oxide memristor crossbars, with device variability sufficiently low to allow operation of integrated neural networks, in a simple network: a single-layer perceptron (an algorithm for linear classification). The network can be taught in situ using a coarse-grain variety of the delta rule algorithm to perform the perfect classification of 3 × 3-pixel black/white images into three classes (representing letters). This demonstration is an important step towards much larger and more complex memristive neuromorphic networks.

Securing Digital Images Integrity using Artificial Neural Networks

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Hajji, Tarik; Itahriouan, Zakaria; Ouazzani Jamil, Mohammed

2018-05-01

Digital image signature is a technique used to protect the image integrity. The application of this technique can serve several areas of imaging applied to smart cities. The objective of this work is to propose two methods to protect digital image integrity. We present a description of two approaches using artificial neural networks (ANN) to digitally sign an image. The first one is “Direct Signature without learning” and the second is “Direct Signature with learning”. This paper presents the theory of proposed approaches and an experimental study to test their effectiveness.

Network propagation in the cytoscape cyberinfrastructure.

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Carlin, Daniel E; Demchak, Barry; Pratt, Dexter; Sage, Eric; Ideker, Trey

2017-10-01

Network propagation is an important and widely used algorithm in systems biology, with applications in protein function prediction, disease gene prioritization, and patient stratification. However, up to this point it has required significant expertise to run. Here we extend the popular network analysis program Cytoscape to perform network propagation as an integrated function. Such integration greatly increases the access to network propagation by putting it in the hands of biologists and linking it to the many other types of network analysis and visualization available through Cytoscape. We demonstrate the power and utility of the algorithm by identifying mutations conferring resistance to Vemurafenib.

Artificial Neural Network Analysis System

Science.gov (United States)

2001-02-27

Contract No. DASG60-00-M-0201 Purchase request no.: Foot in the Door-01 Title Name: Artificial Neural Network Analysis System Company: Atlantic... Artificial Neural Network Analysis System 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Powell, Bruce C 5d. PROJECT NUMBER 5e. TASK NUMBER...34) 27-02-2001 Report Type N/A Dates Covered (from... to) ("DD MON YYYY") 28-10-2000 27-02-2001 Title and Subtitle Artificial Neural Network Analysis

A Belief-Space Approach to Integrated Intelligence - Research Area 10.3: Intelligent Networks

Science.gov (United States)

2017-12-05

A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks The views, opinions and/or findings contained in this...Technology (MIT) Title: A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks Report Term: 0-Other Email: tlp...students presented progress and received feedback from the research group . o wrote papers on their research and submitted them to leading conferences

Integrated Hydrologic Science and Environmental Engineering Observatory: CLEANER's Vision for the WATERS Network

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Montgomery, J. L.; Minsker, B. S.; Schnoor, J.; Haas, C.; Bonner, J.; Driscoll, C.; Eschenbach, E.; Finholt, T.; Glass, J.; Harmon, T.; Johnson, J.; Krupnik, A.; Reible, D.; Sanderson, A.; Small, M.; van Briesen, J.

2006-05-01

With increasing population and urban development, societies grow more and more concerned over balancing the need to maintain adequate water supplies with that of ensuring the quality of surface and groundwater resources. For example, multiple stressors such as overfishing, runoff of nutrients from agricultural fields and confined animal feeding lots, and pathogens in urban stormwater can often overwhelm a single water body. Mitigating just one of these problems often depends on understanding how it relates to others and how stressors can vary in temporal and spatial scales. Researchers are now in a position to answer questions about multiscale, spatiotemporally distributed hydrologic and environmental phenomena through the use of remote and embedded networked sensing technologies. It is now possible for data streaming from sensor networks to be integrated by a rich cyberinfrastructure encompassing the innovative computing, visualization, and information archiving strategies needed to cope with the anticipated onslaught of data, and to turn that data around in the form of real-time water quantity and quality forecasting. Recognizing this potential, NSF awarded $2 million to a coalition of 12 institutions in July 2005 to establish the CLEANER Project Office (Collaborative Large-Scale Engineering Analysis Network for Environmental Research; http://cleaner.ncsa.uiuc.edu). Over the next two years the project office, in coordination with CUAHSI (Consortium of Universities for the Advancement of Hydrologic Science, Inc.; http://www.cuahsi.org), will work together to develop a plan for a WATer and Environmental Research Systems Network (WATERS Network), which is envisioned to be a collaborative scientific exploration and engineering analysis network, using high performance tools and infrastructure, to transform our scientific understanding of how water quantity, quality, and related earth system processes are affected by natural and human-induced changes to the environment

A service-oriented architecture for integrating the modeling and formal verification of genetic regulatory networks

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Page Michel

2009-12-01

Full Text Available Abstract Background The study of biological networks has led to the development of increasingly large and detailed models. Computer tools are essential for the simulation of the dynamical behavior of the networks from the model. However, as the size of the models grows, it becomes infeasible to manually verify the predictions against experimental data or identify interesting features in a large number of simulation traces. Formal verification based on temporal logic and model checking provides promising methods to automate and scale the analysis of the models. However, a framework that tightly integrates modeling and simulation tools with model checkers is currently missing, on both the conceptual and the implementational level. Results We have developed a generic and modular web service, based on a service-oriented architecture, for integrating the modeling and formal verification of genetic regulatory networks. The architecture has been implemented in the context of the qualitative modeling and simulation tool GNA and the model checkers NUSMV and CADP. GNA has been extended with a verification module for the specification and checking of biological properties. The verification module also allows the display and visual inspection of the verification results. Conclusions The practical use of the proposed web service is illustrated by means of a scenario involving the analysis of a qualitative model of the carbon starvation response in E. coli. The service-oriented architecture allows modelers to define the model and proceed with the specification and formal verification of the biological properties by means of a unified graphical user interface. This guarantees a transparent access to formal verification technology for modelers of genetic regulatory networks.

Proposition of a modeling and an analysis methodology of integrated reverse logistics chain in the direct chain

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Faycal Mimouni

2016-04-01

Full Text Available Purpose: Propose a modeling and analysis methodology based on the combination of Bayesian networks and Petri networks of the reverse logistics integrated the direct supply chain. Design/methodology/approach: Network modeling by combining Petri and Bayesian network. Findings: Modeling with Bayesian network complimented with Petri network to break the cycle problem in the Bayesian network. Research limitations/implications: Demands are independent from returns. Practical implications: Model can only be used on nonperishable products. Social implications: Legislation aspects: Recycling laws; Protection of environment; Client satisfaction via after sale service. Originality/value: Bayesian network with a cycle combined with the Petri Network.

Academic self-efficacy, growth mindsets, and university students' integration in academic and social support networks

NARCIS (Netherlands)

Zander, Lysann; Brouwer, Jasperina; Jansen, Ellen; Crayen, Claudia; Hannover, Bettina

Combining complete social networks and structural equation modeling, we investigate how two learning-related cognitions, academic self-efficacy and growth mindsets, relate to integration in support networks of 580 university students in 30 seminar groups. We assessed integration as popularity in

Social Network Analysis and informal trade

DEFF Research Database (Denmark)

Walther, Olivier

networks can be applied to better understand informal trade in developing countries, with a particular focus on Africa. The paper starts by discussing some of the fundamental concepts developed by social network analysis. Through a number of case studies, we show how social network analysis can...... illuminate the relevant causes of social patterns, the impact of social ties on economic performance, the diffusion of resources and information, and the exercise of power. The paper then examines some of the methodological challenges of social network analysis and how it can be combined with other...... approaches. The paper finally highlights some of the applications of social network analysis and their implications for trade policies....

Large-scale modeling of condition-specific gene regulatory networks by information integration and inference.

Science.gov (United States)

Ellwanger, Daniel Christian; Leonhardt, Jörn Florian; Mewes, Hans-Werner

2014-12-01

Understanding how regulatory networks globally coordinate the response of a cell to changing conditions, such as perturbations by shifting environments, is an elementary challenge in systems biology which has yet to be met. Genome-wide gene expression measurements are high dimensional as these are reflecting the condition-specific interplay of thousands of cellular components. The integration of prior biological knowledge into the modeling process of systems-wide gene regulation enables the large-scale interpretation of gene expression signals in the context of known regulatory relations. We developed COGERE (http://mips.helmholtz-muenchen.de/cogere), a method for the inference of condition-specific gene regulatory networks in human and mouse. We integrated existing knowledge of regulatory interactions from multiple sources to a comprehensive model of prior information. COGERE infers condition-specific regulation by evaluating the mutual dependency between regulator (transcription factor or miRNA) and target gene expression using prior information. This dependency is scored by the non-parametric, nonlinear correlation coefficient η(2) (eta squared) that is derived by a two-way analysis of variance. We show that COGERE significantly outperforms alternative methods in predicting condition-specific gene regulatory networks on simulated data sets. Furthermore, by inferring the cancer-specific gene regulatory network from the NCI-60 expression study, we demonstrate the utility of COGERE to promote hypothesis-driven clinical research. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

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Kim Hyun

2011-12-01

Full Text Available Abstract Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network.

Science.gov (United States)

Kim, Hyun Uk; Kim, Tae Yong; Lee, Sang Yup

2011-01-01

Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism's metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

Constructing an integrated gene similarity network for the identification of disease genes.

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Tian, Zhen; Guo, Maozu; Wang, Chunyu; Xing, LinLin; Wang, Lei; Zhang, Yin

2017-09-20

Discovering novel genes that are involved human diseases is a challenging task in biomedical research. In recent years, several computational approaches have been proposed to prioritize candidate disease genes. Most of these methods are mainly based on protein-protein interaction (PPI) networks. However, since these PPI networks contain false positives and only cover less half of known human genes, their reliability and coverage are very low. Therefore, it is highly necessary to fuse multiple genomic data to construct a credible gene similarity network and then infer disease genes on the whole genomic scale. We proposed a novel method, named RWRB, to infer causal genes of interested diseases. First, we construct five individual gene (protein) similarity networks based on multiple genomic data of human genes. Then, an integrated gene similarity network (IGSN) is reconstructed based on similarity network fusion (SNF) method. Finally, we employee the random walk with restart algorithm on the phenotype-gene bilayer network, which combines phenotype similarity network, IGSN as well as phenotype-gene association network, to prioritize candidate disease genes. We investigate the effectiveness of RWRB through leave-one-out cross-validation methods in inferring phenotype-gene relationships. Results show that RWRB is more accurate than state-of-the-art methods on most evaluation metrics. Further analysis shows that the success of RWRB is benefited from IGSN which has a wider coverage and higher reliability comparing with current PPI networks. Moreover, we conduct a comprehensive case study for Alzheimer's disease and predict some novel disease genes that supported by literature. RWRB is an effective and reliable algorithm in prioritizing candidate disease genes on the genomic scale. Software and supplementary information are available at http://nclab.hit.edu.cn/~tianzhen/RWRB/ .

Contingent approach to Internet-based supply network integration

Science.gov (United States)

Ho, Jessica; Boughton, Nick; Kehoe, Dennis; Michaelides, Zenon

2001-10-01

The Internet is playing an increasingly important role in enhancing the operations of supply networks as many organizations begin to recognize the benefits of Internet- enabled supply arrangements. However, the developments and applications to-date do not extend significantly beyond the dyadic model, whereas the real advantages are to be made with the external and network models to support a coordinated and collaborative based approach. The DOMAIN research group at the University of Liverpool is currently defining new Internet- enabled approaches to enable greater collaboration across supply chains. Different e-business models and tools are focusing on different applications. Using inappropriate e- business models, tools or techniques will bring negative results instead of benefits to all the tiers in the supply network. Thus there are a number of issues to be considered before addressing Internet based supply network integration, in particular an understanding of supply chain management, the emergent business models and evaluating the effects of deploying e-business to the supply network or a particular tier. It is important to utilize a contingent approach to selecting the right e-business model to meet the specific supply chain requirements. This paper addresses the issues and provides a case study on the indirect materials supply networks.

Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

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Ajay Kumar Saxena

2002-05-01

Full Text Available Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives postulated by various groups emphasized the need of an intelligent group decision support system approach in this field. In this paper, an Integrated Multimedia based Intelligent Group Decision Support System (IM1GDSS is presented, and its main components are analyzed and discussed. In particular attention is focused on the Data Base, Model Base, Central Black Board (CBB and Multicriteria Futuristic Decision Process (MFDP module. The model base interacts with Electrical Power Network Load Forecasting and Planning (EPNLFP Module; Resource Optimization, Modeling and Simulation (ROMAS Module; Electrical Power Network Control and Evaluation Process (EPNCAEP Module, and MFDP Module through CBB for strategic planning, management control, operational planning and transaction processing. The richness of multimedia channels adds a totally new dimension in a group decision making for Electrical Power Network. The proposed IMIGDSS is a user friendly, highly interactive group decision making system, based on efficient intelligent and multimedia communication support for group discussions, retrieval of content and multi criteria decision analysis.

Construction of an integrated gene regulatory network link to stress-related immune system in cattle.

Science.gov (United States)

Behdani, Elham; Bakhtiarizadeh, Mohammad Reza

2017-10-01

The immune system is an important biological system that is negatively impacted by stress. This study constructed an integrated regulatory network to enhance our understanding of the regulatory gene network used in the stress-related immune system. Module inference was used to construct modules of co-expressed genes with bovine leukocyte RNA-Seq data. Transcription factors (TFs) were then assigned to these modules using Lemon-Tree algorithms. In addition, the TFs assigned to each module were confirmed using the promoter analysis and protein-protein interactions data. Therefore, our integrated method identified three TFs which include one TF that is previously known to be involved in immune response (MYBL2) and two TFs (E2F8 and FOXS1) that had not been recognized previously and were identified for the first time in this study as novel regulatory candidates in immune response. This study provides valuable insights on the regulatory programs of genes involved in the stress-related immune system.

The RETAIN project: DICOM teleradiology over an ATM-based network. Radiological Examinations Transfer on an ATM Integrated Network.

Science.gov (United States)

Heautot, J F; Eichelberg, M; Gibaud, B; Tréguier, C; Lemoine, D; Scarabin, J M; Piqueras, J; Carsin, M; Gandon, Y

2000-01-01

The RETAIN project (Radiological Examinations Transfer on an ATM Integrated Network) has aimed at testing videoconferencing and DICOM image transfers to get advice about difficult radiological cases over an asynchronous transfer mode (ATM)-based network, which affords a more comfortable interface than narrow-band networks and allows exchange of complete image series using the DICOM format of studies. For this purpose, an experimental ATM network was applied between six university hospitals in four different countries. An assessment of the functionalities of the system was performed by means of log-file analysis, video recording of the sessions and forms filled out by the participants at the end of each session. Questionnaires were answered by the users at the end of the project to bring out perspectives of utilisation and added value. We discussed 43 cases during 20 sessions. For technical or organisational problems, only 20 of the 36 planned sessions took place. The throughput over ATM (10.5 Mbit/s, 20 times faster than six ISDN B-channels) was adequate. Despite the experimental configuration of the network, the system was considered as satisfactory by all the physicians. In 72 % of the sessions, the expected result (answer to the question) was gained. By common consent, videoconferencing was unanimously regarded as a prominent tool in improving the interaction quality. Asynchronous transfer mode is an efficient method for fast transferring of radiologic examinations in DICOM format and for discussing them through high-quality videoconferencing.

Passivity analysis for uncertain BAM neural networks with time delays and reaction-diffusions

Science.gov (United States)

Zhou, Jianping; Xu, Shengyuan; Shen, Hao; Zhang, Baoyong

2013-08-01

This article deals with the problem of passivity analysis for delayed reaction-diffusion bidirectional associative memory (BAM) neural networks with weight uncertainties. By using a new integral inequality, we first present a passivity condition for the nominal networks, and then extend the result to the case with linear fractional weight uncertainties. The proposed conditions are expressed in terms of linear matrix inequalities, and thus can be checked easily. Examples are provided to demonstrate the effectiveness of the proposed results.

Analysis of transportation networks subject to natural hazards – Insights from a Colombian case

International Nuclear Information System (INIS)

Muriel-Villegas, Juan E.; Alvarez-Uribe, Karla C.; Patiño-Rodríguez, Carmen E.; Villegas, Juan G.

2016-01-01

This study provides an applied framework to derive the connectivity reliability and vulnerability of inter-urban transportation systems under network disruptions. The proposed model integrates statistical reliability analysis to find the reliability and vulnerability of transportation networks. Most of the modern research in this field has focused on urban networks where the primary concerns are guaranteeing predefined standards of capacity and travel time. However, at a regional and national level, especially in developing countries, the connectivity of remote populations in the case of disaster is of utmost importance. The applicability of the framework is demonstrated with a case study in the state of Antioquia, Colombia, using historical records from the 2010 to 2011 rainy season, an aspect that stands out and gives additional support compared to previous studies that considers simulated data from assumed distributions. The results provide significant insights to practitioners and researchers for the design and management of transportation systems and route planning strategies under this type of disruptions. - Highlights: • Applied framework to derive the connectivity reliability and vulnerability of inter-urban transportation systems. • The model integrates statistical analysis to find the reliability of transportation networks. • An algorithm is proposed to evaluate the vulnerability of the network. • The applicability of the framework is demonstrated with a case study with real data.

Analysis of Recurrent Analog Neural Networks