WorldWideScience

Sample records for cellular signaling networks

  1. Discrete dynamic modeling of cellular signaling networks.

    Science.gov (United States)

    Albert, Réka; Wang, Rui-Sheng

    2009-01-01

    Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

  2. Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks

    Science.gov (United States)

    White, Forest M.; Wolf-Yadlin, Alejandro

    2016-06-01

    Protein phosphorylation-mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks.

  3. [Cellular adhesion signal transduction network of tumor necrosis factor-alpha induced hepatocellular carcinoma cells].

    Science.gov (United States)

    Zheng, Yongchang; Du, Shunda; Xu, Haifeng; Xu, Yiyao; Zhao, Haitao; Chi, Tianyi; Lu, Xin; Sang, Xinting; Mao, Yilei

    2014-11-18

    To systemically explore the cellular adhesion signal transduction network of tumor necrosis factor-alpha (TNF-α)-induced hepatocellular carcinoma cells with bioinformatics tools. Published microarray dataset of TNF-α-induced HepG2, human transcription factor database HTRI and human protein-protein interaction database HPRD were used to construct and analyze the signal transduction network. In the signal transduction network, MYC and SP1 were the key nodes of signaling transduction. Several genes from the network were closely related with cellular adhesion.Epidermal growth factor receptor (EGFR) is a possible key gene of effectively regulating cellular adhesion during the induction of TNF-α. EGFR is a possible key gene for TNF-α-induced metastasis of hepatocellular carcinoma.

  4. Filtering and spectral processing of 1-D signals using cellular neural networks

    NARCIS (Netherlands)

    Moreira-Tamayo, O.; Pineda de Gyvez, J.

    1996-01-01

    This paper presents cellular neural networks (CNN) for one-dimensional discrete signal processing. Although CNN has been extensively used in image processing applications, little has been done for 1-dimensional signal processing. We propose a novel CNN architecture to carry out these tasks. This

  5. Perturbation Biology: Inferring Signaling Networks in Cellular Systems

    Science.gov (United States)

    Miller, Martin L.; Gauthier, Nicholas P.; Jing, Xiaohong; Kaushik, Poorvi; He, Qin; Mills, Gordon; Solit, David B.; Pratilas, Christine A.; Weigt, Martin; Braunstein, Alfredo; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

    2013-01-01

    We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology. PMID:24367245

  6. Assessment of general public exposure to lte signals compared to other cellular networks present in Thessaloniki, Greece

    International Nuclear Information System (INIS)

    Gkonis, Fotios; Boursianis, Achilles; Samaras, Theodoros

    2017-01-01

    To assess general public exposure to electromagnetic fields from Long Term Evolution (LTE) base stations, measurements at 10 sites in Thessaloniki, Greece were performed. Results are compared with other mobile cellular networks currently in use. All exposure values satisfy the guidelines for general public exposure of the International Commission on Non-Ionizing Radiation Protection (ICNIRP), as well as the reference levels by the Greek legislation at all sites. LTE electric field measurements were recorded up to 0.645 V/m. By applying the ICNIRP guidelines, the exposure ratio for all LTE signals is between 2.9 x 10"-"5 and 2.8 x 10"-"2. From the measurements results it is concluded that the average and maximum power density contribution of LTE down-link signals to the overall cellular networks signals are 7.8% and 36.7%, respectively. (authors)

  7. Energy-Efficient Crowdsensing of Human Mobility and Signal Levels in Cellular Networks

    Science.gov (United States)

    Foremski, Paweł; Gorawski, Michał; Grochla, Krzysztof; Polys, Konrad

    2015-01-01

    The paper presents a practical application of the crowdsensing idea to measure human mobility and signal coverage in cellular networks. Currently, virtually everyone is carrying a mobile phone, which may be used as a sensor to gather research data by measuring, e.g., human mobility and radio signal levels. However, many users are unwilling to participate in crowdsensing experiments. This work begins with the analysis of the barriers for engaging people in crowdsensing. A survey showed that people who agree to participate in crowdsensing expect a minimum impact on their battery lifetime and phone usage habits. To address these requirements, this paper proposes an application for measuring the location and signal strength data based on energy-efficient GPS tracking, which allows one to perform the measurements of human mobility and radio signal levels with minimum energy utilization and without any engagement of the user. The method described combines measurements from the accelerometer with effective management of the GPS to monitor the user mobility with the decrease in battery lifetime by approximately 20%. To show the applicability of the proposed platform, the sample results of signal level distribution and coverage maps gathered for an LTE network and representing human mobility are shown. PMID:26340633

  8. Assessment of General Public Exposure to LTE signals compared to other Cellular Networks Present in Thessaloniki, Greece.

    Science.gov (United States)

    Gkonis, Fotios; Boursianis, Achilles; Samaras, Theodoros

    2017-07-01

    To assess general public exposure to electromagnetic fields from Long Term Evolution (LTE) base stations, measurements at 10 sites in Thessaloniki, Greece were performed. Results are compared with other mobile cellular networks currently in use. All exposure values satisfy the guidelines for general public exposure of the International Commission on Non-Ionizing Radiation Protection (ICNIRP), as well as the reference levels by the Greek legislation at all sites. LTE electric field measurements were recorded up to 0.645 V/m. By applying the ICNIRP guidelines, the exposure ratio for all LTE signals is between 2.9 × 10-5 and 2.8 × 10-2. From the measurements results it is concluded that the average and maximum power density contribution of LTE downlink signals to the overall cellular networks signals are 7.8% and 36.7%, respectively. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  9. An empirical Bayesian approach for model-based inference of cellular signaling networks

    Directory of Open Access Journals (Sweden)

    Klinke David J

    2009-11-01

    Full Text Available Abstract Background A common challenge in systems biology is to infer mechanistic descriptions of biological process given limited observations of a biological system. Mathematical models are frequently used to represent a belief about the causal relationships among proteins within a signaling network. Bayesian methods provide an attractive framework for inferring the validity of those beliefs in the context of the available data. However, efficient sampling of high-dimensional parameter space and appropriate convergence criteria provide barriers for implementing an empirical Bayesian approach. The objective of this study was to apply an Adaptive Markov chain Monte Carlo technique to a typical study of cellular signaling pathways. Results As an illustrative example, a kinetic model for the early signaling events associated with the epidermal growth factor (EGF signaling network was calibrated against dynamic measurements observed in primary rat hepatocytes. A convergence criterion, based upon the Gelman-Rubin potential scale reduction factor, was applied to the model predictions. The posterior distributions of the parameters exhibited complicated structure, including significant covariance between specific parameters and a broad range of variance among the parameters. The model predictions, in contrast, were narrowly distributed and were used to identify areas of agreement among a collection of experimental studies. Conclusion In summary, an empirical Bayesian approach was developed for inferring the confidence that one can place in a particular model that describes signal transduction mechanisms and for inferring inconsistencies in experimental measurements.

  10. Modeling virtualized downlink cellular networks with ultra-dense small cells

    KAUST Repository

    Ibrahim, Hazem

    2015-09-11

    The unrelenting increase in the mobile users\\' populations and traffic demand drive cellular network operators to densify their infrastructure. Network densification increases the spatial frequency reuse efficiency while maintaining the signal-to-interference-plus-noise-ratio (SINR) performance, hence, increases the spatial spectral efficiency and improves the overall network performance. However, control signaling in such dense networks consumes considerable bandwidth and limits the densification gain. Radio access network (RAN) virtualization via control plane (C-plane) and user plane (U-plane) splitting has been recently proposed to lighten the control signaling burden and improve the network throughput. In this paper, we present a tractable analytical model for virtualized downlink cellular networks, using tools from stochastic geometry. We then apply the developed modeling framework to obtain design insights for virtualized RANs and quantify associated performance improvement. © 2015 IEEE.

  11. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.

    2013-01-01

    During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more comprehensive modelling studies of hormonal transport and signalling in a multi-scale setting. © EDP Sciences, 2013.

  12. Unified Stochastic Geometry Model for MIMO Cellular Networks with Retransmissions

    KAUST Repository

    Afify, Laila H.

    2016-10-11

    This paper presents a unified mathematical paradigm, based on stochastic geometry, for downlink cellular networks with multiple-input-multiple-output (MIMO) base stations (BSs). The developed paradigm accounts for signal retransmission upon decoding errors, in which the temporal correlation among the signal-to-interference-plus-noise-ratio (SINR) of the original and retransmitted signals is captured. In addition to modeling the effect of retransmission on the network performance, the developed mathematical model presents twofold analysis unification for MIMO cellular networks literature. First, it integrates the tangible decoding error probability and the abstracted (i.e., modulation scheme and receiver type agnostic) outage probability analysis, which are largely disjoint in the literature. Second, it unifies the analysis for different MIMO configurations. The unified MIMO analysis is achieved by abstracting unnecessary information conveyed within the interfering signals by Gaussian signaling approximation along with an equivalent SISO representation for the per-data stream SINR in MIMO cellular networks. We show that the proposed unification simplifies the analysis without sacrificing the model accuracy. To this end, we discuss the diversity-multiplexing tradeoff imposed by different MIMO schemes and shed light on the diversity loss due to the temporal correlation among the SINRs of the original and retransmitted signals. Finally, several design insights are highlighted.

  13. Unified Stochastic Geometry Model for MIMO Cellular Networks with Retransmissions

    KAUST Repository

    Afify, Laila H.; Elsawy, Hesham; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2016-01-01

    This paper presents a unified mathematical paradigm, based on stochastic geometry, for downlink cellular networks with multiple-input-multiple-output (MIMO) base stations (BSs). The developed paradigm accounts for signal retransmission upon decoding errors, in which the temporal correlation among the signal-to-interference-plus-noise-ratio (SINR) of the original and retransmitted signals is captured. In addition to modeling the effect of retransmission on the network performance, the developed mathematical model presents twofold analysis unification for MIMO cellular networks literature. First, it integrates the tangible decoding error probability and the abstracted (i.e., modulation scheme and receiver type agnostic) outage probability analysis, which are largely disjoint in the literature. Second, it unifies the analysis for different MIMO configurations. The unified MIMO analysis is achieved by abstracting unnecessary information conveyed within the interfering signals by Gaussian signaling approximation along with an equivalent SISO representation for the per-data stream SINR in MIMO cellular networks. We show that the proposed unification simplifies the analysis without sacrificing the model accuracy. To this end, we discuss the diversity-multiplexing tradeoff imposed by different MIMO schemes and shed light on the diversity loss due to the temporal correlation among the SINRs of the original and retransmitted signals. Finally, several design insights are highlighted.

  14. Cellular Signaling in Health and Disease

    CERN Document Server

    Beckerman, Martin

    2009-01-01

    In today’s world, three great classes of non-infectious diseases – the metabolic syndromes (such as type 2 diabetes and atherosclerosis), the cancers, and the neurodegenerative disorders – have risen to the fore. These diseases, all associated with increasing age of an individual, have proven to be remarkably complex and difficult to treat. This is because, in large measure, when the cellular signaling pathways responsible for maintaining homeostasis and health of the body become dysregulated, they generate equally stable disease states. As a result the body may respond positively to a drug, but only for a while and then revert back to the disease state. Cellular Signaling in Health and Disease summarizes our current understanding of these regulatory networks in the healthy and diseased states, showing which molecular components might be prime targets for drug interventions. This is accomplished by presenting models that explain in mechanistic, molecular detail how a particular part of the cellular sign...

  15. 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.

  16. Various cellular stress components change as the rat ages: An insight into the putative overall age-related cellular stress network.

    Science.gov (United States)

    Cueno, Marni E; Imai, Kenichi

    2018-02-01

    Cellular stress is mainly comprised of oxidative, nitrosative, and endoplasmic reticulum stresses and has long been correlated to the ageing process. Surprisingly, the age-related difference among the various components in each independent stress pathway and the possible significance of these components in relation to the overall cellular stress network remain to be clearly elucidated. In this study, we obtained blood from ageing rats upon reaching 20-, 40-, and 72-wk.-old. Subsequently, we measured representative cellular stress-linked biomolecules (H 2 O 2 , glutathione reductase, heme, NADPH, NADP, nitric oxide, GADD153) and cell signals [substance P (SP), free fatty acid, calcium, NF-κB] in either or both blood serum and cytosol. Subsequently, network analysis of the overall cellular stress network was performed. Our results show that there are changes affecting stress-linked biomolecules and cell signals as the rat ages. Additionally, based on our network analysis data, we postulate that NADPH, H 2 O 2 , GADD153, and SP are the key components and the interactions between these components are central to the overall age-related cellular stress network in the rat blood. Thus, we propose that the main pathway affecting the overall age-related cellular stress network in the rat blood would entail NADPH-related oxidative stress (involving H 2 O 2 ) triggering GADD153 activation leading to SP induction which in-turn affects other cell signals. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Signal Quality Outage Analysis for Ultra-Reliable Communications in Cellular Networks

    DEFF Research Database (Denmark)

    Gerardino, Guillermo Andrés Pocovi; Alvarez, Beatriz Soret; Lauridsen, Mads

    2015-01-01

    Ultra-reliable communications over wireless will open the possibility for a wide range of novel use cases and applications. In cellular networks, achieving reliable communication is challenging due to many factors, particularly the fading of the desired signal and the interference. In this regard......, we investigate the potential of several techniques to combat these main threats. The analysis shows that traditional microscopic multiple-input multiple-output schemes with 2x2 or 4x4 antenna configurations are not enough to fulfil stringent reliability requirements. It is revealed how such antenna...... schemes must be complemented with macroscopic diversity as well as interference management techniques in order to ensure the necessary SINR outage performance. Based on the obtained performance results, it is discussed which of the feasible options fulfilling the ultra-reliable criteria are most promising...

  18. Heterogeneous cellular networks

    CERN Document Server

    Hu, Rose Qingyang

    2013-01-01

    A timely publication providing coverage of radio resource management, mobility management and standardization in heterogeneous cellular networks The topic of heterogeneous cellular networks has gained momentum in industry and the research community, attracting the attention of standardization bodies such as 3GPP LTE and IEEE 802.16j, whose objectives are looking into increasing the capacity and coverage of the cellular networks. This book focuses on recent progresses,  covering the related topics including scenarios of heterogeneous network deployment, interference management i

  19. Quantitative phosphoproteomics to characterize signaling networks

    DEFF Research Database (Denmark)

    Rigbolt, Kristoffer T G; Blagoev, Blagoy

    2012-01-01

    for analyzing protein phosphorylation at a system-wide scale and has become the intuitive strategy for comprehensive characterization of signaling networks. Contemporary phosphoproteomics use highly optimized procedures for sample preparation, mass spectrometry and data analysis algorithms to identify......Reversible protein phosphorylation is involved in the regulation of most, if not all, major cellular processes via dynamic signal transduction pathways. During the last decade quantitative phosphoproteomics have evolved from a highly specialized area to a powerful and versatile platform...... and quantify thousands of phosphorylations, thus providing extensive overviews of the cellular signaling networks. As a result of these developments quantitative phosphoproteomics have been applied to study processes as diverse as immunology, stem cell biology and DNA damage. Here we review the developments...

  20. Antiviral and Inflammatory Cellular Signaling Associated with Enterovirus 71 Infection

    Directory of Open Access Journals (Sweden)

    Yuefei Jin

    2018-03-01

    Full Text Available Enterovirus 71 (EV71 infection has become a major threat to global public health, especially in infants and young children. Epidemiological studies have indicated that EV71 infection is responsible for severe and even fatal cases of hand, foot, and mouth disease (HFMD. Accumulated evidence indicates that EV71 infection triggers a plethora of interactive signaling pathways, resulting in host immune evasion and inflammatory response. This review mainly covers the effects of EV71 infection on major antiviral and inflammatory cellular signal pathways. EV71 can activate cellular signaling networks including multiple cell surface and intracellular receptors, intracellular kinases, calcium flux, and transcription factors that regulate antiviral innate immunity and inflammatory response. Cellular signaling plays a critical role in the regulation of host innate immune and inflammatory pathogenesis. Elucidation of antiviral and inflammatory cellular signaling pathways initiated by EV71 will not only help uncover the potential mechanisms of EV71 infection-induced pathogenesis, but will also provide clues for the design of therapeutic strategies against EV71 infection.

  1. 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

  2. Experimental and computational tools for analysis of signaling networks in primary cells

    DEFF Research Database (Denmark)

    Schoof, Erwin M; Linding, Rune

    2014-01-01

    Cellular information processing in signaling networks forms the basis of responses to environmental stimuli. At any given time, cells receive multiple simultaneous input cues, which are processed and integrated to determine cellular responses such as migration, proliferation, apoptosis, or differ......Cellular information processing in signaling networks forms the basis of responses to environmental stimuli. At any given time, cells receive multiple simultaneous input cues, which are processed and integrated to determine cellular responses such as migration, proliferation, apoptosis......; this information is critical when trying to elucidate key proteins involved in specific cellular responses. Here, methods to generate high-quality quantitative phosphorylation data from cell lysates originating from primary cells, and how to analyze the generated data to construct quantitative signaling network...

  3. Cellular network entropy as the energy potential in Waddington's differentiation landscape

    Science.gov (United States)

    Banerji, Christopher R. S.; Miranda-Saavedra, Diego; Severini, Simone; Widschwendter, Martin; Enver, Tariq; Zhou, Joseph X.; Teschendorff, Andrew E.

    2013-01-01

    Differentiation is a key cellular process in normal tissue development that is significantly altered in cancer. Although molecular signatures characterising pluripotency and multipotency exist, there is, as yet, no single quantitative mark of a cellular sample's position in the global differentiation hierarchy. Here we adopt a systems view and consider the sample's network entropy, a measure of signaling pathway promiscuity, computable from a sample's genome-wide expression profile. We demonstrate that network entropy provides a quantitative, in-silico, readout of the average undifferentiated state of the profiled cells, recapitulating the known hierarchy of pluripotent, multipotent and differentiated cell types. Network entropy further exhibits dynamic changes in time course differentiation data, and in line with a sample's differentiation stage. In disease, network entropy predicts a higher level of cellular plasticity in cancer stem cell populations compared to ordinary cancer cells. Importantly, network entropy also allows identification of key differentiation pathways. Our results are consistent with the view that pluripotency is a statistical property defined at the cellular population level, correlating with intra-sample heterogeneity, and driven by the degree of signaling promiscuity in cells. In summary, network entropy provides a quantitative measure of a cell's undifferentiated state, defining its elevation in Waddington's landscape. PMID:24154593

  4. Increasing cellular coverage within integrated terrestrial/satellite mobile networks

    Science.gov (United States)

    Castro, Jonathan P.

    1995-01-01

    When applying the hierarchical cellular concept, the satellite acts as giant umbrella cell covering a region with some terrestrial cells. If a mobile terminal traversing the region arrives to the border-line or limits of a regular cellular ground service, network transition occurs and the satellite system continues the mobile coverage. To adequately assess the boundaries of service of a mobile satellite system an a cellular network within an integrated environment, this paper provides an optimized scheme to predict when a network transition may be necessary. Under the assumption of a classified propagation phenomenon and Lognormal shadowing, the study applies an analytical approach to estimate the location of a mobile terminal based on a reception of the signal strength emitted by a base station.

  5. Gene regulatory and signaling networks exhibit distinct topological distributions of motifs

    Science.gov (United States)

    Ferreira, Gustavo Rodrigues; Nakaya, Helder Imoto; Costa, Luciano da Fontoura

    2018-04-01

    The biological processes of cellular decision making and differentiation involve a plethora of signaling pathways and gene regulatory circuits. These networks in turn exhibit a multitude of motifs playing crucial parts in regulating network activity. Here we compare the topological placement of motifs in gene regulatory and signaling networks and observe that it suggests different evolutionary strategies in motif distribution for distinct cellular subnetworks.

  6. Adenylate Kinase and AMP Signaling Networks: Metabolic Monitoring, Signal Communication and Body Energy Sensing

    Directory of Open Access Journals (Sweden)

    Andre Terzic

    2009-04-01

    Full Text Available Adenylate kinase and downstream AMP signaling is an integrated metabolic monitoring system which reads the cellular energy state in order to tune and report signals to metabolic sensors. A network of adenylate kinase isoforms (AK1-AK7 are distributed throughout intracellular compartments, interstitial space and body fluids to regulate energetic and metabolic signaling circuits, securing efficient cell energy economy, signal communication and stress response. The dynamics of adenylate kinase-catalyzed phosphotransfer regulates multiple intracellular and extracellular energy-dependent and nucleotide signaling processes, including excitation-contraction coupling, hormone secretion, cell and ciliary motility, nuclear transport, energetics of cell cycle, DNA synthesis and repair, and developmental programming. Metabolomic analyses indicate that cellular, interstitial and blood AMP levels are potential metabolic signals associated with vital functions including body energy sensing, sleep, hibernation and food intake. Either low or excess AMP signaling has been linked to human disease such as diabetes, obesity and hypertrophic cardiomyopathy. Recent studies indicate that derangements in adenylate kinase-mediated energetic signaling due to mutations in AK1, AK2 or AK7 isoforms are associated with hemolytic anemia, reticular dysgenesis and ciliary dyskinesia. Moreover, hormonal, food and antidiabetic drug actions are frequently coupled to alterations of cellular AMP levels and associated signaling. Thus, by monitoring energy state and generating and distributing AMP metabolic signals adenylate kinase represents a unique hub within the cellular homeostatic network.

  7. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.; Byrne, H.M.; King, J.R.; Bennett, M.J.

    2013-01-01

    methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more

  8. Modeling and Analysis of Cellular Networks using Stochastic Geometry: A Tutorial

    KAUST Repository

    Elsawy, Hesham; Salem, Ahmed Sultan; Alouini, Mohamed-Slim; Win, Moe Z.

    2016-01-01

    This paper presents a tutorial on stochastic geometry (SG) based analysis for cellular networks. This tutorial is distinguished by its depth with respect to wireless communication details and its focus on cellular networks. The paper starts by modeling and analyzing the baseband interference in a baseline single-tier downlink cellular network with single antenna base stations and universal frequency reuse. Then, it characterizes signal-to-interference-plus-noise-ratio (SINR) and its related performance metrics. In particular, a unified approach to conduct error probability, outage probability, and transmission rate analysis is presented. Although the main focus of the paper is on cellular networks, the presented unified approach applies for other types of wireless networks that impose interference protection around receivers. The paper then extends the unified approach to capture cellular network characteristics (e.g., frequency reuse, multiple antenna, power control, etc.). It also presents numerical examples associated with demonstrations and discussions. To this end, the paper highlights the state-of-the- art research and points out future research directions.

  9. Modeling and Analysis of Cellular Networks using Stochastic Geometry: A Tutorial

    KAUST Repository

    Elsawy, Hesham

    2016-11-03

    This paper presents a tutorial on stochastic geometry (SG) based analysis for cellular networks. This tutorial is distinguished by its depth with respect to wireless communication details and its focus on cellular networks. The paper starts by modeling and analyzing the baseband interference in a baseline single-tier downlink cellular network with single antenna base stations and universal frequency reuse. Then, it characterizes signal-to-interference-plus-noise-ratio (SINR) and its related performance metrics. In particular, a unified approach to conduct error probability, outage probability, and transmission rate analysis is presented. Although the main focus of the paper is on cellular networks, the presented unified approach applies for other types of wireless networks that impose interference protection around receivers. The paper then extends the unified approach to capture cellular network characteristics (e.g., frequency reuse, multiple antenna, power control, etc.). It also presents numerical examples associated with demonstrations and discussions. To this end, the paper highlights the state-of-the- art research and points out future research directions.

  10. Boltzmann learning of parameters in cellular neural networks

    DEFF Research Database (Denmark)

    Hansen, Lars Kai

    1992-01-01

    The use of Bayesian methods to design cellular neural networks for signal processing tasks and the Boltzmann machine learning rule for parameter estimation is discussed. The learning rule can be used for models with hidden units, or for completely unsupervised learning. The latter is exemplified...

  11. Error performance analysis in downlink cellular networks with interference management

    KAUST Repository

    Afify, Laila H.

    2015-05-01

    Modeling aggregate network interference in cellular networks has recently gained immense attention both in academia and industry. While stochastic geometry based models have succeeded to account for the cellular network geometry, they mostly abstract many important wireless communication system aspects (e.g., modulation techniques, signal recovery techniques). Recently, a novel stochastic geometry model, based on the Equivalent-in-Distribution (EiD) approach, succeeded to capture the aforementioned communication system aspects and extend the analysis to averaged error performance, however, on the expense of increasing the modeling complexity. Inspired by the EiD approach, the analysis developed in [1] takes into consideration the key system parameters, while providing a simple tractable analysis. In this paper, we extend this framework to study the effect of different interference management techniques in downlink cellular network. The accuracy of the proposed analysis is verified via Monte Carlo simulations.

  12. MIMO Communication for Cellular Networks

    CERN Document Server

    Huang, Howard; Venkatesan, Sivarama

    2012-01-01

    As the theoretical foundations of multiple-antenna techniques evolve and as these multiple-input multiple-output (MIMO) techniques become essential for providing high data rates in wireless systems, there is a growing need to understand the performance limits of MIMO in practical networks. To address this need, MIMO Communication for Cellular Networks presents a systematic description of MIMO technology classes and a framework for MIMO system design that takes into account the essential physical-layer features of practical cellular networks. In contrast to works that focus on the theoretical performance of abstract MIMO channels, MIMO Communication for Cellular Networks emphasizes the practical performance of realistic MIMO systems. A unified set of system simulation results highlights relative performance gains of different MIMO techniques and provides insights into how best to use multiple antennas in cellular networks under various conditions. MIMO Communication for Cellular Networks describes single-user,...

  13. The Influence of Gaussian Signaling Approximation on Error Performance in Cellular Networks

    KAUST Repository

    Afify, Laila H.; Elsawy, Hesham; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2015-01-01

    Stochastic geometry analysis for cellular networks is mostly limited to outage probability and ergodic rate, which abstracts many important wireless communication aspects. Recently, a novel technique based on the Equivalent-in-Distribution (EiD) approach is proposed to extend the analysis to capture these metrics and analyze bit error probability (BEP) and symbol error probability (SEP). However, the EiD approach considerably increases the complexity of the analysis. In this paper, we propose an approximate yet accurate framework, that is also able to capture fine wireless communication details similar to the EiD approach, but with simpler analysis. The proposed methodology is verified against the exact EiD analysis in both downlink and uplink cellular networks scenarios.

  14. The Influence of Gaussian Signaling Approximation on Error Performance in Cellular Networks

    KAUST Repository

    Afify, Laila H.

    2015-08-18

    Stochastic geometry analysis for cellular networks is mostly limited to outage probability and ergodic rate, which abstracts many important wireless communication aspects. Recently, a novel technique based on the Equivalent-in-Distribution (EiD) approach is proposed to extend the analysis to capture these metrics and analyze bit error probability (BEP) and symbol error probability (SEP). However, the EiD approach considerably increases the complexity of the analysis. In this paper, we propose an approximate yet accurate framework, that is also able to capture fine wireless communication details similar to the EiD approach, but with simpler analysis. The proposed methodology is verified against the exact EiD analysis in both downlink and uplink cellular networks scenarios.

  15. [Cell signaling pathways interaction in cellular proliferation: Potential target for therapeutic interventionism].

    Science.gov (United States)

    Valdespino-Gómez, Víctor Manuel; Valdespino-Castillo, Patricia Margarita; Valdespino-Castillo, Víctor Edmundo

    2015-01-01

    Nowadays, cellular physiology is best understood by analysing their interacting molecular components. Proteins are the major components of the cells. Different proteins are organised in the form of functional clusters, pathways or networks. These molecules are ordered in clusters of receptor molecules of extracellular signals, transducers, sensors and biological response effectors. The identification of these intracellular signaling pathways in different cellular types has required a long journey of experimental work. More than 300 intracellular signaling pathways have been identified in human cells. They participate in cell homeostasis processes for structural and functional maintenance. Some of them participate simultaneously or in a nearly-consecutive progression to generate a cellular phenotypic change. In this review, an analysis is performed on the main intracellular signaling pathways that take part in the cellular proliferation process, and the potential use of some components of these pathways as target for therapeutic interventionism are also underlined. Copyright © 2015 Academia Mexicana de Cirugía A.C. Published by Masson Doyma México S.A. All rights reserved.

  16. Stochastic effects as a force to increase the complexity of signaling networks

    KAUST Repository

    Kuwahara, Hiroyuki

    2013-07-29

    Cellular signaling networks are complex and appear to include many nonfunctional elements. Recently, it was suggested that nonfunctional interactions of proteins cause signaling noise, which, perhaps, shapes the signal transduction mechanism. However, the conditions under which molecular noise influences cellular information processing remain unclear. Here, we explore a large number of simple biological models of varying network sizes to understand the architectural conditions under which the interactions of signaling proteins can exhibit specific stochastic effects - called deviant effects - in which the average behavior of a biological system is substantially altered in the presence of molecular noise. We find that a small fraction of these networks does exhibit deviant effects and shares a common architectural feature whereas most of the networks show only insignificant levels of deviations. Interestingly, addition of seemingly unimportant interactions into protein networks gives rise to deviant effects.

  17. Coordination of Heparan Sulfate Proteoglycans with Wnt Signaling To Control Cellular Migrations and Positioning in Caenorhabditis elegans.

    Science.gov (United States)

    Saied-Santiago, Kristian; Townley, Robert A; Attonito, John D; da Cunha, Dayse S; Díaz-Balzac, Carlos A; Tecle, Eillen; Bülow, Hannes E

    2017-08-01

    Heparan sulfates (HS) are linear polysaccharides with complex modification patterns, which are covalently bound via conserved attachment sites to core proteins to form heparan sulfate proteoglycans (HSPGs). HSPGs regulate many aspects of the development and function of the nervous system, including cell migration, morphology, and network connectivity. HSPGs function as cofactors for multiple signaling pathways, including the Wnt-signaling molecules and their Frizzled receptors. To investigate the functional interactions among the HSPG and Wnt networks, we conducted genetic analyses of each, and also between these networks using five cellular migrations in the nematode Caenorhabditis elegans We find that HSPG core proteins act genetically in a combinatorial fashion dependent on the cellular contexts. Double mutant analyses reveal distinct redundancies among HSPGs for different migration events, and different cellular migrations require distinct heparan sulfate modification patterns. Our studies reveal that the transmembrane HSPG SDN-1/Syndecan functions within the migrating cell to promote cellular migrations, while the GPI-linked LON-2/Glypican functions cell nonautonomously to establish the final cellular position. Genetic analyses with the Wnt-signaling system show that (1) a given HSPG can act with different Wnts and Frizzled receptors, and that (2) a given Wnt/Frizzled pair acts with different HSPGs in a context-dependent manner. Lastly, we find that distinct HSPG and Wnt/Frizzled combinations serve separate functions to promote cellular migration and establish position of specific neurons. Our studies suggest that HSPGs use structurally diverse glycans in coordination with Wnt-signaling pathways to control multiple cellular behaviors, including cellular and axonal migrations and, cellular positioning. Copyright © 2017 by the Genetics Society of America.

  18. From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

    Science.gov (United States)

    Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

    2016-03-14

    The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

  19. Prediction Based Energy Balancing Forwarding in Cellular Networks

    Directory of Open Access Journals (Sweden)

    Yang Jian-Jun

    2017-01-01

    Full Text Available In the recent cellular network technologies, relay stations extend cell coverage and enhance signal strength for mobile users. However, busy traffic makes the relay stations in hot area run out of energy quickly. Energy is a very important factor in the forwarding of cellular network since mobile users(cell phones in hot cells often suffer from low throughput due to energy lack problems. In many situations, the energy lack problems take place because the energy loading is not balanced. In this paper, we present a prediction based forwarding algorithm to let a mobile node dynamically select the next relay station with highest potential energy capacity to resume communication. Key to this strategy is that a relay station only maintains three past status, and then it is able to predict the potential energy capacity. Then, the node selects the next hop with potential maximal energy. Moreover, a location based algorithm is developed to let the mobile node figure out the target region in order to avoid flooding. Simulations demonstrate that our approach significantly increase the aggregate throughput and decrease the delay in cellular network environment.

  20. Evolution of SH2 domains and phosphotyrosine signalling networks

    Science.gov (United States)

    Liu, Bernard A.; Nash, Piers D.

    2012-01-01

    Src homology 2 (SH2) domains mediate selective protein–protein interactions with tyrosine phosphorylated proteins, and in doing so define specificity of phosphotyrosine (pTyr) signalling networks. SH2 domains and protein-tyrosine phosphatases expand alongside protein-tyrosine kinases (PTKs) to coordinate cellular and organismal complexity in the evolution of the unikont branch of the eukaryotes. Examination of conserved families of PTKs and SH2 domain proteins provides fiduciary marks that trace the evolutionary landscape for the development of complex cellular systems in the proto-metazoan and metazoan lineages. The evolutionary provenance of conserved SH2 and PTK families reveals the mechanisms by which diversity is achieved through adaptations in tissue-specific gene transcription, altered ligand binding, insertions of linear motifs and the gain or loss of domains following gene duplication. We discuss mechanisms by which pTyr-mediated signalling networks evolve through the development of novel and expanded families of SH2 domain proteins and the elaboration of connections between pTyr-signalling proteins. These changes underlie the variety of general and specific signalling networks that give rise to tissue-specific functions and increasingly complex developmental programmes. Examination of SH2 domains from an evolutionary perspective provides insight into the process by which evolutionary expansion and modification of molecular protein interaction domain proteins permits the development of novel protein-interaction networks and accommodates adaptation of signalling networks. PMID:22889907

  1. Molecular and Cellular Signaling

    CERN Document Server

    Beckerman, Martin

    2005-01-01

    A small number of signaling pathways, no more than a dozen or so, form a control layer that is responsible for all signaling in and between cells of the human body. The signaling proteins belonging to the control layer determine what kinds of cells are made during development and how they function during adult life. Malfunctions in the proteins belonging to the control layer are responsible for a host of human diseases ranging from neurological disorders to cancers. Most drugs target components in the control layer, and difficulties in drug design are intimately related to the architecture of the control layer. Molecular and Cellular Signaling provides an introduction to molecular and cellular signaling in biological systems with an emphasis on the underlying physical principles. The text is aimed at upper-level undergraduates, graduate students and individuals in medicine and pharmacology interested in broadening their understanding of how cells regulate and coordinate their core activities and how diseases ...

  2. 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.

  3. Estimating cellular network performance during hurricanes

    International Nuclear Information System (INIS)

    Booker, Graham; Torres, Jacob; Guikema, Seth; Sprintson, Alex; Brumbelow, Kelly

    2010-01-01

    Cellular networks serve a critical role during and immediately after a hurricane, allowing citizens to contact emergency services when land-line communication is lost and serving as a backup communication channel for emergency responders. However, due to their ubiquitous deployment and limited design for extreme loading events, basic network elements, such as cellular towers and antennas are prone to failures during adverse weather conditions such as hurricanes. Accordingly, a systematic and computationally feasible approach is required for assessing and improving the reliability of cellular networks during hurricanes. In this paper we develop a new multi-disciplinary approach to efficiently and accurately assess cellular network reliability during hurricanes. We show how the performance of a cellular network during and immediately after future hurricanes can be estimated based on a combination of hurricane wind field models, structural reliability analysis, Monte Carlo simulation, and cellular network models and simulation tools. We then demonstrate the use of this approach for assessing the improvement in system reliability that can be achieved with discrete topological changes in the system. Our results suggest that adding redundancy, particularly through a mesh topology or through the addition of an optical fiber ring around the perimeter of the system can be an effective way to significantly increase the reliability of some cellular systems during hurricanes.

  4. Admission Control Threshold in Cellular Relay Networks with Power Adjustment

    Directory of Open Access Journals (Sweden)

    Lee Ki-Dong

    2009-01-01

    Full Text Available Abstract In the cellular network with relays, the mobile station can benefit from both coverage extension and capacity enhancement. However, the operation complexity increases as the number of relays grows up. Furthermore, in the cellular network with cooperative relays, it is even more complex because of an increased dimension of signal-to-noise ratios (SNRs formed in the cooperative wireless transmission links. In this paper, we propose a new method for admission capacity planning in a cellular network using a cooperative relaying mechanism called decode-and-forward. We mathematically formulate the dropping ratio using the randomness of "channel gain." With this, we formulate an admission threshold planning problem as a simple optimization problem, where we maximize the accommodation capacity (in number of connections subject to two types of constraints. (1 A constraint that the sum of the transmit powers of the source node and relay node is upper-bounded where both nodes can jointly adjust the transmit power. (2 A constraint that the dropping ratio is upper-bounded by a certain threshold value. The simplicity of the problem formulation facilitates its solution in real-time. We believe that the proposed planning method can provide an attractive guideline for dimensioning a cellular relay network with cooperative relays.

  5. Stochastic effects as a force to increase the complexity of signaling networks

    KAUST Repository

    Kuwahara, Hiroyuki; Gao, Xin

    2013-01-01

    Cellular signaling networks are complex and appear to include many nonfunctional elements. Recently, it was suggested that nonfunctional interactions of proteins cause signaling noise, which, perhaps, shapes the signal transduction mechanism

  6. Environment Aware Cellular Networks

    KAUST Repository

    Ghazzai, Hakim

    2015-02-01

    The unprecedented rise of mobile user demand over the years have led to an enormous growth of the energy consumption of wireless networks as well as the greenhouse gas emissions which are estimated currently to be around 70 million tons per year. This significant growth of energy consumption impels network companies to pay huge bills which represent around half of their operating expenditures. Therefore, many service providers, including mobile operators, are looking for new and modern green solutions to help reduce their expenses as well as the level of their CO2 emissions. Base stations are the most power greedy element in cellular networks: they drain around 80% of the total network energy consumption even during low traffic periods. Thus, there is a growing need to develop more energy-efficient techniques to enhance the green performance of future 4G/5G cellular networks. Due to the problem of traffic load fluctuations in cellular networks during different periods of the day and between different areas (shopping or business districts and residential areas), the base station sleeping strategy has been one of the main popular research topics in green communications. In this presentation, we present several practical green techniques that provide significant gains for mobile operators. Indeed, combined with the base station sleeping strategy, these techniques achieve not only a minimization of the fossil fuel consumption but also an enhancement of mobile operator profits. We start with an optimized cell planning method that considers varying spatial and temporal user densities. We then use the optimal transport theory in order to define the cell boundaries such that the network total transmit power is reduced. Afterwards, we exploit the features of the modern electrical grid, the smart grid, as a new tool of power management for cellular networks and we optimize the energy procurement from multiple energy retailers characterized by different prices and pollutant

  7. Reconstruction of cellular signal transduction networks using perturbation assays and linear programming.

    Science.gov (United States)

    Knapp, Bettina; Kaderali, Lars

    2013-01-01

    Perturbation experiments for example using RNA interference (RNAi) offer an attractive way to elucidate gene function in a high throughput fashion. The placement of hit genes in their functional context and the inference of underlying networks from such data, however, are challenging tasks. One of the problems in network inference is the exponential number of possible network topologies for a given number of genes. Here, we introduce a novel mathematical approach to address this question. We formulate network inference as a linear optimization problem, which can be solved efficiently even for large-scale systems. We use simulated data to evaluate our approach, and show improved performance in particular on larger networks over state-of-the art methods. We achieve increased sensitivity and specificity, as well as a significant reduction in computing time. Furthermore, we show superior performance on noisy data. We then apply our approach to study the intracellular signaling of human primary nave CD4(+) T-cells, as well as ErbB signaling in trastuzumab resistant breast cancer cells. In both cases, our approach recovers known interactions and points to additional relevant processes. In ErbB signaling, our results predict an important role of negative and positive feedback in controlling the cell cycle progression.

  8. Cell Identification based on Received Signal Strength Fingerprints: Concept and Application towards Energy Saving in Cellular Networks

    Directory of Open Access Journals (Sweden)

    Elke Roth-Mandutz

    2014-09-01

    Full Text Available The increasing deployment of small cells aimed at off-loading data traffic from macrocells in heterogeneous networks has resulted in a drastic increase in energy consumption in cellular networks. Energy consumption can be optimized in a selforganized way by adapting the number of active cells in response to the current traffic demand. In this paper we concentrate on the complex problem of how to identify small cells to be reactivated in situations where multiple cells are concurrently inactive. Solely based on the received signal strength, we present cell-specific patterns for the generation of unique cell fingerprints. The cell fingerprints of the deactivated cells are matched with measurements from a high data rate demanding mobile device to identify the most appropriate candidate. Our scheme results in a matching success rate of up to 100% to identify the best cell depending on the number of cells to be activated.

  9. Spectral and Energy Efficiencies in mmWave Cellular Networks for Optimal Utilization

    Directory of Open Access Journals (Sweden)

    Abdulbaset M. Hamed

    2018-01-01

    Full Text Available Millimeter wave (mmWave spectrum has been proposed for use in commercial cellular networks to relieve the already severely congested microwave spectrum. Thus, the design of an efficient mmWave cellular network has gained considerable importance and has to take into account regulations imposed by government agencies with regard to global warming and sustainable development. In this paper, a dense mmWave hexagonal cellular network with each cell consisting of a number of smaller cells with their own Base Stations (BSs is presented as a solution to meet the increasing demand for a variety of high data rate services and growing number of users of cellular networks. Since spectrum and power are critical resources in the design of such a network, a framework is presented that addresses efficient utilization of these resources in mmWave cellular networks in the 28 and 73 GHz bands. These bands are already an integral part of well-known standards such as IEEE 802.15.3c, IEEE 802.11ad, and IEEE 802.16.1. In the analysis, a well-known accurate mmWave channel model for Line of Sight (LOS and Non-Line of Sight (NLOS links is used. The cellular network is analyzed in terms of spectral efficiency, bit/s, energy efficiency, bit/J, area spectral efficiency, bit/s/m2, area energy efficiency, bit/J/m2, and network latency, s/bit. These efficiency metrics are illustrated, using Monte Carlo simulation, as a function of Signal-to-Noise Ratio (SNR, channel model parameters, user distance from BS, and BS transmission power. The efficiency metrics for optimum deployment of cellular networks in 28 and 73 GHz bands are identified. Results show that 73 GHz band achieves better spectrum efficiency and the 28 GHz band is superior in terms of energy efficiency. It is observed that while the latter band is expedient for indoor networks, the former band is appropriate for outdoor networks.

  10. Biosensor Architectures for High-Fidelity Reporting of Cellular Signaling

    Science.gov (United States)

    Dushek, Omer; Lellouch, Annemarie C.; Vaux, David J.; Shahrezaei, Vahid

    2014-01-01

    Understanding mechanisms of information processing in cellular signaling networks requires quantitative measurements of protein activities in living cells. Biosensors are molecular probes that have been developed to directly track the activity of specific signaling proteins and their use is revolutionizing our understanding of signal transduction. The use of biosensors relies on the assumption that their activity is linearly proportional to the activity of the signaling protein they have been engineered to track. We use mechanistic mathematical models of common biosensor architectures (single-chain FRET-based biosensors), which include both intramolecular and intermolecular reactions, to study the validity of the linearity assumption. As a result of the classic mechanism of zero-order ultrasensitivity, we find that biosensor activity can be highly nonlinear so that small changes in signaling protein activity can give rise to large changes in biosensor activity and vice versa. This nonlinearity is abolished in architectures that favor the formation of biosensor oligomers, but oligomeric biosensors produce complicated FRET states. Based on this finding, we show that high-fidelity reporting is possible when a single-chain intermolecular biosensor is used that cannot undergo intramolecular reactions and is restricted to forming dimers. We provide phase diagrams that compare various trade-offs, including observer effects, which further highlight the utility of biosensor architectures that favor intermolecular over intramolecular binding. We discuss challenges in calibrating and constructing biosensors and highlight the utility of mathematical models in designing novel probes for cellular signaling. PMID:25099816

  11. Cancer signaling networks and their implications for personalized medicine

    DEFF Research Database (Denmark)

    Creixell, Pau

    Amongst the unique features of cancer cells perhaps the most crucial one is the change in the cellular decision-making process. While both non-cancer and cancer cells are constantly integrating different external cues that reach them and computing cellular decisions (e.g. proliferation or apoptosis......) based on the integration of these cues; this integration and consequently the cellular decisions taken by cancer cells are arguably very distinct from the decisions that would be expected from non-cancer cells. Since cellular signaling networks and its different states are the computational circuits...

  12. Tolerance to drought and salt stress in plants: Unraveling the signaling networks

    Directory of Open Access Journals (Sweden)

    Dortje eGolldack

    2014-04-01

    Full Text Available Tolerance of plants to abiotic stressors such as drought and salinity is triggered by complex multicomponent signaling pathways to restore cellular homeostasis and promote survival. Major plant transcription factor families such as bZIP, NAC, AP2/ERF and MYB orchestrate regulatory networks underlying abiotic stress tolerance. Sucrose nonfermenting 1-related protein kinase 2 (SnRK2 and MAPK pathways contribute to initiation of stress adaptive downstream responses and promote plant growth and development. As a convergent point of multiple abiotic cues, cellular effects of environmental stresses are not only imbalances of ionic and osmotic homeostasis but also impaired photosynthesis, cellular energy depletion, and redox imbalances. Recent evidence of regulatory systems that link sensing and signaling of environmental conditions and the intracellular redox status have shed light on interfaces of stress and energy signaling. ROS (reactive oxygen species cause severe cellular damage by peroxidation and de-esterification of membrane lipids, however, current models also define a pivotal signaling function of ROS in triggering tolerance against stress. Recent research advances suggest and support a regulatory role of ROS in the cross talks of stress triggered hormonal signaling such as the abscisic acid (ABA pathway and endogenously induced redox and metabolite signals. Here, we discuss and review the versatile molecular convergence in the abiotic stress responsive signaling networks in the context of ROS and lipid derived signals and the specific role of stomatal signaling.

  13. Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles

    Directory of Open Access Journals (Sweden)

    Shah Imran

    2011-07-01

    Full Text Available Abstract Background With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate the physiological effect of chemicals, including potential toxicity. Here we investigate a biologically motivated model for estimating tissue level responses by aggregating the behavior of a cell population. We assume that the molecular state of individual cells is independently governed by discrete non-deterministic signaling mechanisms. This results in noisy but highly reproducible aggregate level responses that are consistent with experimental data. Results We developed an asynchronous threshold Boolean network simulation algorithm to model signal transduction in a single cell, and then used an ensemble of these models to estimate the aggregate response across a cell population. Using published data, we derived a putative crosstalk network involving growth factors and cytokines - i.e., Epidermal Growth Factor, Insulin, Insulin like Growth Factor Type 1, and Tumor Necrosis Factor α - to describe early signaling events in cell proliferation signal transduction. Reproducibility of the modeling technique across ensembles of Boolean networks representing cell populations is investigated. Furthermore, we compare our simulation results to experimental observations of hepatocytes reported in the literature. Conclusion A systematic analysis of the results following differential stimulation of this model by growth factors and cytokines suggests that: (a using Boolean network ensembles with asynchronous updating provides biologically plausible noisy individual cellular responses with reproducible mean behavior for large cell populations, and (b with sufficient data our model can estimate the response to different concentrations of extracellular ligands. Our

  14. Virtualized cognitive network architecture for 5G cellular networks

    KAUST Repository

    Elsawy, Hesham

    2015-07-17

    Cellular networks have preserved an application agnostic and base station (BS) centric architecture1 for decades. Network functionalities (e.g. user association) are decided and performed regardless of the underlying application (e.g. automation, tactile Internet, online gaming, multimedia). Such an ossified architecture imposes several hurdles against achieving the ambitious metrics of next generation cellular systems. This article first highlights the features and drawbacks of such architectural ossification. Then the article proposes a virtualized and cognitive network architecture, wherein network functionalities are implemented via software instances in the cloud, and the underlying architecture can adapt to the application of interest as well as to changes in channels and traffic conditions. The adaptation is done in terms of the network topology by manipulating connectivities and steering traffic via different paths, so as to attain the applications\\' requirements and network design objectives. The article presents cognitive strategies to implement some of the classical network functionalities, along with their related implementation challenges. The article further presents a case study illustrating the performance improvement of the proposed architecture as compared to conventional cellular networks, both in terms of outage probability and handover rate.

  15. Attractor Structures of Signaling Networks: Consequences of Different Conformational Barcode Dynamics and Their Relations to Network-Based Drug Design.

    Science.gov (United States)

    Szalay, Kristóf Z; Nussinov, Ruth; Csermely, Peter

    2014-06-01

    Conformational barcodes tag functional sites of proteins and are decoded by interacting molecules transmitting the incoming signal. Conformational barcodes are modified by all co-occurring allosteric events induced by post-translational modifications, pathogen, drug binding, etc. We argue that fuzziness (plasticity) of conformational barcodes may be increased by disordered protein structures, by integrative plasticity of multi-phosphorylation events, by increased intracellular water content (decreased molecular crowding) and by increased action of molecular chaperones. This leads to increased plasticity of signaling and cellular networks. Increased plasticity is both substantiated by and inducing an increased noise level. Using the versatile network dynamics tool, Turbine (www.turbine.linkgroup.hu), here we show that the 10 % noise level expected in cellular systems shifts a cancer-related signaling network of human cells from its proliferative attractors to its largest, apoptotic attractor representing their health-preserving response in the carcinogen containing and tumor suppressor deficient environment modeled in our study. Thus, fuzzy conformational barcodes may not only make the cellular system more plastic, and therefore more adaptable, but may also stabilize the complex system allowing better access to its largest attractor. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Unified tractable model for downlink MIMO cellular networks using stochastic geometry

    KAUST Repository

    Afify, Laila H.

    2016-07-26

    Several research efforts are invested to develop stochastic geometry models for cellular networks with multiple antenna transmission and reception (MIMO). On one hand, there are models that target abstract outage probability and ergodic rate for simplicity. On the other hand, there are models that sacrifice simplicity to target more tangible performance metrics such as the error probability. Both types of models are completely disjoint in terms of the analytic steps to obtain the performance measures, which makes it challenging to conduct studies that account for different performance metrics. This paper unifies both techniques and proposes a unified stochastic-geometry based mathematical paradigm to account for error probability, outage probability, and ergodic rates in MIMO cellular networks. The proposed model is also unified in terms of the antenna configurations and leads to simpler error probability analysis compared to existing state-of-the-art models. The core part of the analysis is based on abstracting unnecessary information conveyed within the interfering signals by assuming Gaussian signaling. To this end, the accuracy of the proposed framework is verified against state-of-the-art models as well as system level simulations. We provide via this unified study insights on network design by reflecting system parameters effect on different performance metrics. © 2016 IEEE.

  17. Best Signal Quality in Cellular Networks: Asymptotic Properties and Applications to Mobility Management in Small Cell Networks

    Directory of Open Access Journals (Sweden)

    Baccelli François

    2010-01-01

    Full Text Available The quickly increasing data traffic and the user demand for a full coverage of mobile services anywhere and anytime are leading mobile networking into a future of small cell networks. However, due to the high-density and randomness of small cell networks, there are several technical challenges. In this paper, we investigate two critical issues: best signal quality and mobility management. Under the assumptions that base stations are uniformly distributed in a ring-shaped region and that shadowings are lognormal, independent, and identically distributed, we prove that when the number of sites in the ring tends to infinity, then (i the maximum signal strength received at the center of the ring tends in distribution to a Gumbel distribution when properly renormalized, and (ii it is asymptotically independent of the interference. Using these properties, we derive the distribution of the best signal quality. Furthermore, an optimized random cell scanning scheme is proposed, based on the evaluation of the optimal number of sites to be scanned for maximizing the user data throughput.

  18. Performance Evaluation Of Mobile Cellular Networks In Nigeria

    OpenAIRE

    Shoewu, O.O

    2018-01-01

    The aim of this paper is to evaluate the performance of mobile networks such as MTN, GLO, and ETISALAT in Nigeria and suggest ways the performance of digital cellular networks can improve to minimize some of its present short comings or limitations. This paper discusses the performance improvement of digital cellular networks. A non- CDMA cellular network is use in an overall wireless environment for the purpose of this paper. This paper also discusses the performance assessment of three mobi...

  19. Base Station Ordering for Emergency Call Localization in Ultra-dense Cellular Networks

    KAUST Repository

    Elsawy, Hesham

    2017-10-04

    This paper proposes the base station ordering localization technique (BoLT) for emergency call localization in cellular networks. Exploiting the foreseen ultra-densification of the next-generation (5G and beyond) cellular networks, we utilize higher-order Voronoi tessellations to provide ubiquitous localization services that are in compliance to the public safety standards in cellular networks. The proposed localization algorithm runs at the base stations (BSs) and requires minimal operation from agents (i.e., mobile users). Particularly, BoLT requires each agent to feedback a neighbor cell list (NCL) that contains the order of neighboring BSs based on the received signal power in the pilots sent from these BSs. Moreover, this paper utilizes stochastic geometry to develop a tractable mathematical model to assess the performance of BoLT in a general network setting. The goal of this paper is to answer the following two fundamental questions: i) how many BSs should be ordered and reported by the agent to achieve a desirable localization accuracy? and ii) what is the localization error probability given that the pilot signals are subject to shadowing? Assuming that the BSs are deployed according to a Poisson point process (PPP), we answer these two questions via characterizing the tradeoff between the area of location region (ALR) and the localization error probability in terms of the number of BSs ordered by the agent. The results show that reporting the order of six neighboring BSs is sufficient to localize the agent within 10% of the cell area. Increasing the number of reported BSs to ten confines the location region to 1% of the cell area. This would translate to the range of a few meters to decimeters in the foreseen ultra-dense 5G networks.

  20. Base Station Ordering for Emergency Call Localization in Ultra-dense Cellular Networks

    KAUST Repository

    Elsawy, Hesham; Dai, Wenhan; Alouini, Mohamed-Slim; Win, Moe Z.

    2017-01-01

    This paper proposes the base station ordering localization technique (BoLT) for emergency call localization in cellular networks. Exploiting the foreseen ultra-densification of the next-generation (5G and beyond) cellular networks, we utilize higher-order Voronoi tessellations to provide ubiquitous localization services that are in compliance to the public safety standards in cellular networks. The proposed localization algorithm runs at the base stations (BSs) and requires minimal operation from agents (i.e., mobile users). Particularly, BoLT requires each agent to feedback a neighbor cell list (NCL) that contains the order of neighboring BSs based on the received signal power in the pilots sent from these BSs. Moreover, this paper utilizes stochastic geometry to develop a tractable mathematical model to assess the performance of BoLT in a general network setting. The goal of this paper is to answer the following two fundamental questions: i) how many BSs should be ordered and reported by the agent to achieve a desirable localization accuracy? and ii) what is the localization error probability given that the pilot signals are subject to shadowing? Assuming that the BSs are deployed according to a Poisson point process (PPP), we answer these two questions via characterizing the tradeoff between the area of location region (ALR) and the localization error probability in terms of the number of BSs ordered by the agent. The results show that reporting the order of six neighboring BSs is sufficient to localize the agent within 10% of the cell area. Increasing the number of reported BSs to ten confines the location region to 1% of the cell area. This would translate to the range of a few meters to decimeters in the foreseen ultra-dense 5G networks.

  1. Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning.

    Science.gov (United States)

    Sohn, Insoo; Liu, Huaping; Ansari, Nirwan

    2015-01-01

    An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction.

  2. Mapping the follicle-stimulating hormone-induced signalling networks

    Directory of Open Access Journals (Sweden)

    Pauline eGloaguen

    2011-10-01

    Full Text Available Follicle-stimulating hormone (FSH is a central regulator of male and female reproductive function. Over the last decade, there has been a growing perception of the complexity associated with FSH-induced cellular signalling. It is now clear that the canonical Gs/cAMP/PKA pathway is not the sole mechanism that must be considered in FSH biological actions. In parallel, consistent with the emerging concept of biased agonism, several examples of ligand-mediated selective signalling pathway activation by gonadotropin receptors have been reported. In this context, it is important to gain an integrative view of the signalling pathways induced by FSH and how they interconnect to form a network. In this review, we propose a first attempt at building topological maps of various pathways known to be involved in the FSH-induced signalling network. We discuss the multiple facets of FSH-induced signalling and how they converge to the hormone integrated biological response. Despite of their incompleteness, these maps of the FSH-induced signalling network represent a first step towards gaining a system-level comprehension of this hormone’s actions, which may ultimately facilitate the discovery of novel regulatory processes and therapeutic strategies for infertilities and non-steroidal contraception.

  3. 1,4-Naphthoquinones: From Oxidative Damage to Cellular and Inter-Cellular Signaling

    Directory of Open Access Journals (Sweden)

    Lars-Oliver Klotz

    2014-09-01

    Full Text Available Naphthoquinones may cause oxidative stress in exposed cells and, therefore, affect redox signaling. Here, contributions of redox cycling and alkylating properties of quinones (both natural and synthetic, such as plumbagin, juglone, lawsone, menadione, methoxy-naphthoquinones, and others to cellular and inter-cellular signaling processes are discussed: (i naphthoquinone-induced Nrf2-dependent modulation of gene expression and its potentially beneficial outcome; (ii the modulation of receptor tyrosine kinases, such as the epidermal growth factor receptor by naphthoquinones, resulting in altered gap junctional intercellular communication. Generation of reactive oxygen species and modulation of redox signaling are properties of naphthoquinones that render them interesting leads for the development of novel compounds of potential use in various therapeutic settings.

  4. Dynamic spectrum management in green cognitive radio cellular networks

    KAUST Repository

    Sboui, Lokman; Ghazzai, Hakim; Rezki, Zouheir; Alouini, Mohamed-Slim

    2018-01-01

    In this paper, we propose a new cellular network operation scheme fulfilling the 5G requirements related to spectrum management and green communications. We focus on cognitive radio cellular networks in which both the primary network (PN

  5. Device-Relaying in Cellular D2D Networks: A Fairness Perspective

    KAUST Repository

    Chaaban, Anas

    2015-10-24

    Device-to-Device (D2D) communication is envisioned to play a key role in 5G networks as a technique for meeting the demand for high data rates. In a cellular network, D2D allows not only direct communication between users, but also device relaying. In this paper, a simple instance of device-relaying is investigated, and its impact on fairness among users is studied. Namely, a cellular network consisting of two D2D-enabled users and a base-station (BS) is considered. Thus, the users who want to establish communication with the BS can act as relays for each other’s signals. While this problem is traditionally considered in the literature as a multiple-access channel with cooperation in the uplink, and a broadcast channel with cooperation in the downlink, we propose a different treatment of the problem as a multi-way channel. A simple communication scheme is proposed, and is shown to achieve significant gain in terms of fairness (measured by the symmetric rate supported) in comparison to the aforementioned traditional treatment.

  6. Device-Relaying in Cellular D2D Networks: A Fairness Perspective

    KAUST Repository

    Chaaban, Anas; Sezgin, Aydin

    2015-01-01

    Device-to-Device (D2D) communication is envisioned to play a key role in 5G networks as a technique for meeting the demand for high data rates. In a cellular network, D2D allows not only direct communication between users, but also device relaying. In this paper, a simple instance of device-relaying is investigated, and its impact on fairness among users is studied. Namely, a cellular network consisting of two D2D-enabled users and a base-station (BS) is considered. Thus, the users who want to establish communication with the BS can act as relays for each other’s signals. While this problem is traditionally considered in the literature as a multiple-access channel with cooperation in the uplink, and a broadcast channel with cooperation in the downlink, we propose a different treatment of the problem as a multi-way channel. A simple communication scheme is proposed, and is shown to achieve significant gain in terms of fairness (measured by the symmetric rate supported) in comparison to the aforementioned traditional treatment.

  7. MSAT and cellular hybrid networking

    Science.gov (United States)

    Baranowsky, Patrick W., II

    Westinghouse Electric Corporation is developing both the Communications Ground Segment and the Series 1000 Mobile Phone for American Mobile Satellite Corporation's (AMSC's) Mobile Satellite (MSAT) system. The success of the voice services portion of this system depends, to some extent, upon the interoperability of the cellular network and the satellite communication circuit switched communication channels. This paper will describe the set of user-selectable cellular interoperable modes (cellular first/satellite second, etc.) provided by the Mobile Phone and described how they are implemented with the ground segment. Topics including roaming registration and cellular-to-satellite 'seamless' call handoff will be discussed, along with the relevant Interim Standard IS-41 Revision B Cellular Radiotelecommunications Intersystem Operations and IOS-553 Mobile Station - Land Station Compatibility Specification.

  8. Systematic identification of cellular signals reactivating Kaposi sarcoma-associated herpesvirus.

    Directory of Open Access Journals (Sweden)

    Fuqu Yu

    2007-03-01

    Full Text Available The herpesvirus life cycle has two distinct phases: latency and lytic replication. The balance between these two phases is critical for viral pathogenesis. It is believed that cellular signals regulate the switch from latency to lytic replication. To systematically evaluate the cellular signals regulating this reactivation process in Kaposi sarcoma-associated herpesvirus, the effects of 26,000 full-length cDNA expression constructs on viral reactivation were individually assessed in primary effusion lymphoma-derived cells that harbor the latent virus. A group of diverse cellular signaling proteins were identified and validated in their effect of inducing viral lytic gene expression from the latent viral genome. The results suggest that multiple cellular signaling pathways can reactivate the virus in a genetically homogeneous cell population. Further analysis revealed that the Raf/MEK/ERK/Ets-1 pathway mediates Ras-induced reactivation. The same pathway also mediates spontaneous reactivation, which sets the first example to our knowledge of a specific cellular pathway being studied in the spontaneous reactivation process. Our study provides a functional genomic approach to systematically identify the cellular signals regulating the herpesvirus life cycle, thus facilitating better understanding of a fundamental issue in virology and identifying novel therapeutic targets.

  9. Signaling by Cellular Protrusions: Keeping the Conversation Private.

    Science.gov (United States)

    Buszczak, Michael; Inaba, Mayu; Yamashita, Yukiko M

    2016-07-01

    Information exchange between different cells makes multicellular life possible. Signaling between cells can occur over long distances, as in the case of hormone signaling, or it can take place over short distances between immediately juxtaposed neighbors, as in the case of stem cell-niche signaling. The ability of signal-sending and -receiving cells to communicate with one another in a specific manner is of paramount importance in the proper development and function of tissues. Growing evidence indicates that different cellular protrusions help to achieve specificity in signaling that occurs between distinct cell types. Here, we focus on new roles for cellular protrusions in cell-to-cell communication, drawing special attention to how stem cells use specialized extensions to promote reception of self-renewing signals emanating from the niche. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Handover management in dense cellular networks: A stochastic geometry approach

    KAUST Repository

    Arshad, Rabe; Elsawy, Hesham; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2016-01-01

    Cellular operators are continuously densifying their networks to cope with the ever-increasing capacity demand. Furthermore, an extreme densification phase for cellular networks is foreseen to fulfill the ambitious fifth generation (5G) performance requirements. Network densification improves spectrum utilization and network capacity by shrinking base stations' (BSs) footprints and reusing the same spectrum more frequently over the spatial domain. However, network densification also increases the handover (HO) rate, which may diminish the capacity gains for mobile users due to HO delays. In highly dense 5G cellular networks, HO delays may neutralize or even negate the gains offered by network densification. In this paper, we present an analytical paradigm, based on stochastic geometry, to quantify the effect of HO delay on the average user rate in cellular networks. To this end, we propose a flexible handover scheme to reduce HO delay in case of highly dense cellular networks. This scheme allows skipping the HO procedure with some BSs along users' trajectories. The performance evaluation and testing of this scheme for only single HO skipping shows considerable gains in many practical scenarios. © 2016 IEEE.

  11. Handover management in dense cellular networks: A stochastic geometry approach

    KAUST Repository

    Arshad, Rabe

    2016-07-26

    Cellular operators are continuously densifying their networks to cope with the ever-increasing capacity demand. Furthermore, an extreme densification phase for cellular networks is foreseen to fulfill the ambitious fifth generation (5G) performance requirements. Network densification improves spectrum utilization and network capacity by shrinking base stations\\' (BSs) footprints and reusing the same spectrum more frequently over the spatial domain. However, network densification also increases the handover (HO) rate, which may diminish the capacity gains for mobile users due to HO delays. In highly dense 5G cellular networks, HO delays may neutralize or even negate the gains offered by network densification. In this paper, we present an analytical paradigm, based on stochastic geometry, to quantify the effect of HO delay on the average user rate in cellular networks. To this end, we propose a flexible handover scheme to reduce HO delay in case of highly dense cellular networks. This scheme allows skipping the HO procedure with some BSs along users\\' trajectories. The performance evaluation and testing of this scheme for only single HO skipping shows considerable gains in many practical scenarios. © 2016 IEEE.

  12. Analysis And Augmentation Of Timing Advance Based Geolocation In Lte Cellular Networks

    Science.gov (United States)

    2016-12-01

    measurements to validate TA-based positioning approaches in LTE . Their approach did not, however, focus on characterizing the TA. Rather, similar to...UE will measure the time difference of arrival of the LTE Positioning Reference Signal (PRS) from multiple eNBs. This information is then sent to a...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA DISSERTATION ANALYSIS AND AUGMENTATION OF TIMING ADVANCE-BASED GEOLOCATION IN LTE CELLULAR NETWORKS by

  13. Error performance analysis in downlink cellular networks with interference management

    KAUST Repository

    Afify, Laila H.; Elsawy, Hesham; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2015-01-01

    Modeling aggregate network interference in cellular networks has recently gained immense attention both in academia and industry. While stochastic geometry based models have succeeded to account for the cellular network geometry, they mostly

  14. Muscle biopsies off-set normal cellular signaling in surrounding musculature

    DEFF Research Database (Denmark)

    Krag, Thomas O; Hauerslev, Simon; Dahlqvist, Julia R

    2013-01-01

    muscle tissue for at least 3 weeks after the biopsy was performed and magnetic resonance imaging suggests that an effect of a biopsy may persist for at least 5 months. Cellular signaling after a biopsy resembles what is seen in severe limb-girdle muscular dystrophy type 2I with respect to protein......Studies of muscle physiology and muscular disorders often require muscle biopsies to answer questions about muscle biology. In this context, we have often wondered if muscle biopsies, especially if performed repeatedly, would affect interpretation of muscle morphology and cellular signaling. We...... hypothesized that muscle morphology and cellular signaling involved in myogenesis/regeneration and protein turnover can be changed by a previous muscle biopsy in close proximity to the area under investigation. Here we report a case where a past biopsy or biopsies affect cellular signaling of the surrounding...

  15. Reverse engineering GTPase programming languages with reconstituted signaling networks.

    Science.gov (United States)

    Coyle, Scott M

    2016-07-02

    The Ras superfamily GTPases represent one of the most prolific signaling currencies used in Eukaryotes. With these remarkable molecules, evolution has built GTPase networks that control diverse cellular processes such as growth, morphology, motility and trafficking. (1-4) Our knowledge of the individual players that underlie the function of these networks is deep; decades of biochemical and structural data has provided a mechanistic understanding of the molecules that turn GTPases ON and OFF, as well as how those GTPase states signal by controlling the assembly of downstream effectors. However, we know less about how these different activities work together as a system to specify complex dynamic signaling outcomes. Decoding this molecular "programming language" would help us understand how different species and cell types have used the same GTPase machinery in different ways to accomplish different tasks, and would also provide new insights as to how mutations to these networks can cause disease. We recently developed a bead-based microscopy assay to watch reconstituted H-Ras signaling systems at work under arbitrary configurations of regulators and effectors. (5) Here we highlight key observations and insights from this study and propose extensions to our method to further study this and other GTPase signaling systems.

  16. Image Encryption and Chaotic Cellular Neural Network

    Science.gov (United States)

    Peng, Jun; Zhang, Du

    Machine learning has been playing an increasingly important role in information security and assurance. One of the areas of new applications is to design cryptographic systems by using chaotic neural network due to the fact that chaotic systems have several appealing features for information security applications. In this chapter, we describe a novel image encryption algorithm that is based on a chaotic cellular neural network. We start by giving an introduction to the concept of image encryption and its main technologies, and an overview of the chaotic cellular neural network. We then discuss the proposed image encryption algorithm in details, which is followed by a number of security analyses (key space analysis, sensitivity analysis, information entropy analysis and statistical analysis). The comparison with the most recently reported chaos-based image encryption algorithms indicates that the algorithm proposed in this chapter has a better security performance. Finally, we conclude the chapter with possible future work and application prospects of the chaotic cellular neural network in other information assurance and security areas.

  17. Existence and exponential stability of almost periodic solution for stochastic cellular neural networks with delay

    International Nuclear Information System (INIS)

    Huang Zaitang; Yang Qigui

    2009-01-01

    The paper considers the problems of existence of quadratic mean almost periodic and global exponential stability for stochastic cellular neural networks with delays. By employing the Holder's inequality and fixed points principle, we present some new criteria ensuring existence and uniqueness of a quadratic mean almost periodic and global exponential stability. These criteria are important in signal processing and the design of networks. Moreover, these criteria are also applied in others stochastic biological neural systems.

  18. Error performance analysis in K-tier uplink cellular networks using a stochastic geometric approach

    KAUST Repository

    Afify, Laila H.

    2015-09-14

    In this work, we develop an analytical paradigm to analyze the average symbol error probability (ASEP) performance of uplink traffic in a multi-tier cellular network. The analysis is based on the recently developed Equivalent-in-Distribution approach that utilizes stochastic geometric tools to account for the network geometry in the performance characterization. Different from the other stochastic geometry models adopted in the literature, the developed analysis accounts for important communication system parameters and goes beyond signal-to-interference-plus-noise ratio characterization. That is, the presented model accounts for the modulation scheme, constellation type, and signal recovery techniques to model the ASEP. To this end, we derive single integral expressions for the ASEP for different modulation schemes due to aggregate network interference. Finally, all theoretical findings of the paper are verified via Monte Carlo simulations.

  19. Channel Asymmetry in Cellular OFDMA-TDD Networks

    Directory of Open Access Journals (Sweden)

    Agyapong Patrick

    2008-01-01

    Full Text Available Abstract This paper studies time division duplex- (TDD- specific interference issues in orthogonal frequency division multiple access- (OFDMA- TDD cellular networks arising from various uplink (UL/downlink (DL traffic asymmetries, considering both line-of-sight (LOS and non-LOS (NLOS conditions among base stations (BSs. The study explores aspects both of channel allocation and user scheduling. In particular, a comparison is drawn between the fixed slot allocation (FSA technique and a dynamic channel allocation (DCA technique for different UL/DL loads. For the latter, random time slot opposing (RTSO is assumed due to its simplicity and its low signaling overhead. Both channel allocation techniques do not obviate the need for user scheduling algorithms, therefore, a greedy and a fair scheduling approach are applied to both the RTSO and the FSA. The systems are evaluated based on spectral efficiency, subcarrier utilization, and user outage. The results show that RTSO networks with DL-favored traffic asymmetries outperform FSA networks for all considered metrics and are robust to LOS between BSs. In addition, it is demonstrated that the greedy scheduling algorithm only offers a marginal increase in spectral efficiency as compared to the fair scheduling algorithm, while the latter exhibits up to 20% lower outage.

  20. 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.

  1. DMPD: Cellular signaling in macrophage migration and chemotaxis. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 11073096 Cellular signaling in macrophage migration and chemotaxis. Jones GE. J Leu...koc Biol. 2000 Nov;68(5):593-602. (.png) (.svg) (.html) (.csml) Show Cellular signaling in macrophage migration... and chemotaxis. PubmedID 11073096 Title Cellular signaling in macrophage migration and chemotaxis. Autho

  2. Collaborative Multi-Layer Network Coding in Hybrid Cellular Cognitive Radio Networks

    KAUST Repository

    Moubayed, Abdallah J.; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2015-01-01

    In this paper, as an extension to [1], we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in hybrid (interweave and underlay) cellular cognitive radio networks. This scheme allows the uncoordinated

  3. Collaborative Multi-Layer Network Coding For Hybrid Cellular Cognitive Radio Networks

    KAUST Repository

    Moubayed, Abdallah J.

    2014-01-01

    In this thesis, as an extension to [1], we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in hybrid (interweave and underlay) cellular cognitive radio networks. This scheme allows the uncoordinated

  4. Cellular signaling identifiability analysis: a case study.

    Science.gov (United States)

    Roper, Ryan T; Pia Saccomani, Maria; Vicini, Paolo

    2010-05-21

    Two primary purposes for mathematical modeling in cell biology are (1) simulation for making predictions of experimental outcomes and (2) parameter estimation for drawing inferences from experimental data about unobserved aspects of biological systems. While the former purpose has become common in the biological sciences, the latter is less common, particularly when studying cellular and subcellular phenomena such as signaling-the focus of the current study. Data are difficult to obtain at this level. Therefore, even models of only modest complexity can contain parameters for which the available data are insufficient for estimation. In the present study, we use a set of published cellular signaling models to address issues related to global parameter identifiability. That is, we address the following question: assuming known time courses for some model variables, which parameters is it theoretically impossible to estimate, even with continuous, noise-free data? Following an introduction to this problem and its relevance, we perform a full identifiability analysis on a set of cellular signaling models using DAISY (Differential Algebra for the Identifiability of SYstems). We use our analysis to bring to light important issues related to parameter identifiability in ordinary differential equation (ODE) models. We contend that this is, as of yet, an under-appreciated issue in biological modeling and, more particularly, cell biology. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  5. Regulation of cellular communication by signaling microdomains in the blood vessel wall.

    Science.gov (United States)

    Billaud, Marie; Lohman, Alexander W; Johnstone, Scott R; Biwer, Lauren A; Mutchler, Stephanie; Isakson, Brant E

    2014-01-01

    It has become increasingly clear that the accumulation of proteins in specific regions of the plasma membrane can facilitate cellular communication. These regions, termed signaling microdomains, are found throughout the blood vessel wall where cellular communication, both within and between cell types, must be tightly regulated to maintain proper vascular function. We will define a cellular signaling microdomain and apply this definition to the plethora of means by which cellular communication has been hypothesized to occur in the blood vessel wall. To that end, we make a case for three broad areas of cellular communication where signaling microdomains could play an important role: 1) paracrine release of free radicals and gaseous molecules such as nitric oxide and reactive oxygen species; 2) role of ion channels including gap junctions and potassium channels, especially those associated with the endothelium-derived hyperpolarization mediated signaling, and lastly, 3) mechanism of exocytosis that has considerable oversight by signaling microdomains, especially those associated with the release of von Willebrand factor. When summed, we believe that it is clear that the organization and regulation of signaling microdomains is an essential component to vessel wall function.

  6. Regulation of Cellular Communication by Signaling Microdomains in the Blood Vessel Wall

    Science.gov (United States)

    Billaud, Marie; Lohman, Alexander W.; Johnstone, Scott R.; Biwer, Lauren A.; Mutchler, Stephanie; Isakson, Brant E.

    2014-01-01

    It has become increasingly clear that the accumulation of proteins in specific regions of the plasma membrane can facilitate cellular communication. These regions, termed signaling microdomains, are found throughout the blood vessel wall where cellular communication, both within and between cell types, must be tightly regulated to maintain proper vascular function. We will define a cellular signaling microdomain and apply this definition to the plethora of means by which cellular communication has been hypothesized to occur in the blood vessel wall. To that end, we make a case for three broad areas of cellular communication where signaling microdomains could play an important role: 1) paracrine release of free radicals and gaseous molecules such as nitric oxide and reactive oxygen species; 2) role of ion channels including gap junctions and potassium channels, especially those associated with the endothelium-derived hyperpolarization mediated signaling, and lastly, 3) mechanism of exocytosis that has considerable oversight by signaling microdomains, especially those associated with the release of von Willebrand factor. When summed, we believe that it is clear that the organization and regulation of signaling microdomains is an essential component to vessel wall function. PMID:24671377

  7. Effects of multiple enzyme–substrate interactions in basic units of cellular signal processing

    International Nuclear Information System (INIS)

    Seaton, D D; Krishnan, J

    2012-01-01

    Covalent modification cycles are a ubiquitous feature of cellular signalling networks. In these systems, the interaction of an active enzyme with the unmodified form of its substrate is essential for signalling to occur. However, this interaction is not necessarily the only enzyme–substrate interaction possible. In this paper, we analyse the behaviour of a basic model of signalling in which additional, non-essential enzyme–substrate interactions are possible. These interactions include those between the inactive form of an enzyme and its substrate, and between the active form of an enzyme and its product. We find that these additional interactions can result in increased sensitivity and biphasic responses, respectively. The dynamics of the responses are also significantly altered by the presence of additional interactions. Finally, we evaluate the consequences of these interactions in two variations of our basic model, involving double modification of substrate and scaffold-mediated signalling, respectively. We conclude that the molecular details of protein–protein interactions are important in determining the signalling properties of enzymatic signalling pathways. (paper)

  8. Network features and pathway analyses of a signal transduction cascade

    Directory of Open Access Journals (Sweden)

    Ryoji Yanashima

    2009-05-01

    Full Text Available The scale-free and small-world network models reflect the functional units of networks. However, when we investigated the network properties of a signaling pathway using these models, no significant differences were found between the original undirected graphs and the graphs in which inactive proteins were eliminated from the gene expression data. We analyzed signaling networks by focusing on those pathways that best reflected cellular function. Therefore, our analysis of pathways started from the ligands and progressed to transcription factors and cytoskeletal proteins. We employed the Python module to assess the target network. This involved comparing the original and restricted signaling cascades as a directed graph using microarray gene expression profiles of late onset Alzheimer's disease. The most commonly used method of shortest-path analysis neglects to consider the influences of alternative pathways that can affect the activation of transcription factors or cytoskeletal proteins. We therefore introduced included k-shortest paths and k-cycles in our network analysis using the Python modules, which allowed us to attain a reasonable computational time and identify k-shortest paths. This technique reflected results found in vivo and identified pathways not found when shortest path or degree analysis was applied. Our module enabled us to comprehensively analyse the characteristics of biomolecular networks and also enabled analysis of the effects of diseases considering the feedback loop and feedforward loop control structures as an alternative path.

  9. Tension and robustness in multitasking cellular networks.

    Directory of Open Access Journals (Sweden)

    Jeffrey V Wong

    Full Text Available Cellular networks multitask by exhibiting distinct, context-dependent dynamics. However, network states (parameters that generate a particular dynamic are often sub-optimal for others, defining a source of "tension" between them. Though multitasking is pervasive, it is not clear where tension arises, what consequences it has, and how it is resolved. We developed a generic computational framework to examine the source and consequences of tension between pairs of dynamics exhibited by the well-studied RB-E2F switch regulating cell cycle entry. We found that tension arose from task-dependent shifts in parameters associated with network modules. Although parameter sets common to distinct dynamics did exist, tension reduced both their accessibility and resilience to perturbation, indicating a trade-off between "one-size-fits-all" solutions and robustness. With high tension, robustness can be preserved by dynamic shifting of modules, enabling the network to toggle between tasks, and by increasing network complexity, in this case by gene duplication. We propose that tension is a general constraint on the architecture and operation of multitasking biological networks. To this end, our work provides a framework to quantify the extent of tension between any network dynamics and how it affects network robustness. Such analysis would suggest new ways to interfere with network elements to elucidate the design principles of cellular networks.

  10. Robust network topologies for generating switch-like cellular responses.

    Directory of Open Access Journals (Sweden)

    Najaf A Shah

    2011-06-01

    Full Text Available Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity and extent of memory (bistability. Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability. Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28% and bistability (up to 18%; strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3% or bistable (up to 1% responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.

  11. Full-Duplex Communications in Large-Scale Cellular Networks

    KAUST Repository

    Alammouri, Ahmad

    2016-01-01

    /downlink interference. This thesis presents a tractable framework, based on stochastic geometry, to study FD communications in multi-tier cellular networks. Particularly, we assess the FD communications effect on the network performance and quantify the associated gains

  12. Quantitative proteomic assessment of very early cellular signaling events

    DEFF Research Database (Denmark)

    Dengjel, Joern; Akimov, Vyacheslav; Olsen, Jesper V

    2007-01-01

    Technical limitations have prevented proteomic analyses of events occurring less than 30 s after signal initiation. We developed an automated, continuous quench-flow system allowing quantitative proteomic assessment of very early cellular signaling events (qPACE) with a time resolution of 1 s...

  13. Energy management in wireless cellular and ad-hoc networks

    CERN Document Server

    Imran, Muhammad; Qaraqe, Khalid; Alouini, Mohamed-Slim; Vasilakos, Athanasios

    2016-01-01

    This book investigates energy management approaches for energy efficient or energy-centric system design and architecture and presents end-to-end energy management in the recent heterogeneous-type wireless network medium. It also considers energy management in wireless sensor and mesh networks by exploiting energy efficient transmission techniques and protocols. and explores energy management in emerging applications, services and engineering to be facilitated with 5G networks such as WBANs, VANETS and Cognitive networks. A special focus of the book is on the examination of the energy management practices in emerging wireless cellular and ad hoc networks. Considering the broad scope of energy management in wireless cellular and ad hoc networks, this book is organized into six sections covering range of Energy efficient systems and architectures; Energy efficient transmission and techniques; Energy efficient applications and services. .

  14. Optimized Energy Procurement for Cellular Networks with Uncertain Renewable Energy Generation

    KAUST Repository

    Rached, Nadhir B.; Ghazzai, Hakim; Kadri, Abdullah; Alouini, Mohamed-Slim

    2017-01-01

    Renewable energy (RE) is an emerging solution for reducing carbon dioxide (CO2) emissions from cellular networks. One of the challenges of using RE sources is to handle its inherent uncertainty. In this paper, a RE powered cellular network

  15. Velocity-Aware Handover Management in Two-Tier Cellular Networks

    KAUST Repository

    Arshad, Rabe; Elsawy, Hesham; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2017-01-01

    by network densification. Hence, user mobility imposes a nontrivial challenge to harvest capacity gains via network densification. In this paper, we propose a velocity-aware HO management scheme for two-tier downlink cellular network to mitigate the HO effect

  16. Wi-Fi Hotspot Auto-Discovery: A Practical & Energy-Aware System for Smart Objects using Cellular Signals

    Directory of Open Access Journals (Sweden)

    Nithyananthan Poosamani

    2015-08-01

    Full Text Available The Internet of Things (IoT paradigm aims to interconnect a variety of heterogeneous Smart Objects (SO using energy-efficient methodologies and standard communication protocols. A majority of consumer devices sold today come equipped with wireless LAN and cellular technology to connect with the world-wide network. To discover Wi-Fi hot spots, there is a need for constant scanning of Wi-Fi radio in these devices and results in significant battery drain. We present PRiSM, a practical system to automatically locate Wi-Fi hotspots while Wi-Fi radio is turned off, by using the statistical characteristics of cellular signals. Cellular signals are received at zero extra cost in mobile devices and hence PRiSM is highly energy-efficient. It is a lightweight client-side only implementation and needs no prior knowledge on floor plans or wireless infrastructure. We implement PRiSM on Android-based devices and show up to 96% of energy savings in Wi-Fi sensing operations which is equivalent to saving up to 16% of total battery capacity, together with an average prediction accuracy of up to 98%.

  17. Toward Continental-scale Rainfall Monitoring Using Commercial Microwave Links From Cellular Communication Networks

    Science.gov (United States)

    Uijlenhoet, R.; Leijnse, H.; Overeem, A.

    2017-12-01

    Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal's attenuation between transmitter and receiver. We have previously shown how one such a network can be used to retrieve the space-time dynamics of rainfall for an entire country (The Netherlands, ˜35,500 km2), based on an unprecedented number of links (˜2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrated the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. The presentation will focus on the potential for upscaling this technique to continental-scale rainfall monitoring in Europe. In addition, several examples of recent applications of this technique on other continents (South America, Africa, Asia and Australia) will be given.

  18. Assessing the implications of cellular network performance on mobile content access

    DEFF Research Database (Denmark)

    Kaup, Fabian; Michelinakis, Foivos; Bui, Nicola

    2016-01-01

    Mobile applications such as VoIP, (live) gaming, or video streaming have diverse QoS requirements ranging from low delay to high throughput. The optimization of the network quality experienced by end-users requires detailed knowledge of the expected network performance. Also, the achieved service...... of cellular network measurements, focused on analyzing root causes of mobile network performance variability. Measurements conducted on a 4G cellular network in Germany show that management and configuration decisions have a substantial impact on the performance. Specifically, it is observed...

  19. Signal Processing and Neural Network Simulator

    Science.gov (United States)

    Tebbe, Dennis L.; Billhartz, Thomas J.; Doner, John R.; Kraft, Timothy T.

    1995-04-01

    The signal processing and neural network simulator (SPANNS) is a digital signal processing simulator with the capability to invoke neural networks into signal processing chains. This is a generic tool which will greatly facilitate the design and simulation of systems with embedded neural networks. The SPANNS is based on the Signal Processing WorkSystemTM (SPWTM), a commercial-off-the-shelf signal processing simulator. SPW provides a block diagram approach to constructing signal processing simulations. Neural network paradigms implemented in the SPANNS include Backpropagation, Kohonen Feature Map, Outstar, Fully Recurrent, Adaptive Resonance Theory 1, 2, & 3, and Brain State in a Box. The SPANNS was developed by integrating SAIC's Industrial Strength Neural Networks (ISNN) Software into SPW.

  20. Dynamic Bayesian Network Modeling of the Interplay between EGFR and Hedgehog Signaling.

    Science.gov (United States)

    Fröhlich, Holger; Bahamondez, Gloria; Götschel, Frank; Korf, Ulrike

    2015-01-01

    Aberrant activation of sonic Hegdehog (SHH) signaling has been found to disrupt cellular differentiation in many human cancers and to increase proliferation. The SHH pathway is known to cross-talk with EGFR dependent signaling. Recent studies experimentally addressed this interplay in Daoy cells, which are presumable a model system for medulloblastoma, a highly malignant brain tumor that predominately occurs in children. Currently ongoing are several clinical trials for different solid cancers, which are designed to validate the clinical benefits of targeting the SHH in combination with other pathways. This has motivated us to investigate interactions between EGFR and SHH dependent signaling in greater depth. To our knowledge, there is no mathematical model describing the interplay between EGFR and SHH dependent signaling in medulloblastoma so far. Here we come up with a fully probabilistic approach using Dynamic Bayesian Networks (DBNs). To build our model, we made use of literature based knowledge describing SHH and EGFR signaling and integrated gene expression (Illumina) and cellular location dependent time series protein expression data (Reverse Phase Protein Arrays). We validated our model by sub-sampling training data and making Bayesian predictions on the left out test data. Our predictions focusing on key transcription factors and p70S6K, showed a high level of concordance with experimental data. Furthermore, the stability of our model was tested by a parametric bootstrap approach. Stable network features were in agreement with published data. Altogether we believe that our model improved our understanding of the interplay between two highly oncogenic signaling pathways in Daoy cells. This may open new perspectives for the future therapy of Hedghog/EGF-dependent solid tumors.

  1. Signaling pathway networks mined from human pituitary adenoma proteomics data

    Directory of Open Access Journals (Sweden)

    Zhan Xianquan

    2010-04-01

    pituitary control related to gene expression and cellular development, and no canonical toxicity pathways were identified. Conclusions This pathway network analysis demonstrated that mitochondrial dysfunction, oxidative stress, cell-cycle dysregulation, and the MAPK-signaling abnormality are significantly associated with a pituitary adenoma. These pathway-network data provide new insights into the molecular mechanisms of human pituitary adenoma pathogenesis, and new clues for an in-depth investigation of pituitary adenoma and biomarker discovery.

  2. Selfish cellular networks and the evolution of complex organisms.

    Science.gov (United States)

    Kourilsky, Philippe

    2012-03-01

    Human gametogenesis takes years and involves many cellular divisions, particularly in males. Consequently, gametogenesis provides the opportunity to acquire multiple de novo mutations. A significant portion of these is likely to impact the cellular networks linking genes, proteins, RNA and metabolites, which constitute the functional units of cells. A wealth of literature shows that these individual cellular networks are complex, robust and evolvable. To some extent, they are able to monitor their own performance, and display sufficient autonomy to be termed "selfish". Their robustness is linked to quality control mechanisms which are embedded in and act upon the individual networks, thereby providing a basis for selection during gametogenesis. These selective processes are equally likely to affect cellular functions that are not gamete-specific, and the evolution of the most complex organisms, including man, is therefore likely to occur via two pathways: essential housekeeping functions would be regulated and evolve during gametogenesis within the parents before being transmitted to their progeny, while classical selection would operate on other traits of the organisms that shape their fitness with respect to the environment. Copyright © 2012 Académie des sciences. Published by Elsevier SAS. All rights reserved.

  3. Path searching in switching networks using cellular algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Koczy, L T; Langer, J; Legendi, T

    1981-01-01

    After a survey of the important statements in the paper A Mathematical Model of Path Searching in General Type Switching Networks (see IBID., vol.25, no.1, p.31-43, 1981) the authors consider the possible implementation for cellular automata of the algorithm introduced there. The cellular field used consists of 5 neighbour 8 state cells. Running times required by a traditional serial processor and by the cellular field, respectively, are compared. By parallel processing this running time can be reduced. 5 references.

  4. Resource allocation for phantom cellular networks: Energy efficiency vs spectral efficiency

    KAUST Repository

    Abdelhady, Amr Mohamed Abdelaziz; Amin, Osama; Alouini, Mohamed-Slim

    2016-01-01

    Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Mean-while, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that finds the SE and EE resource allocation strategies for phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and phantom cells share of the total number of available resource blocks. We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It was found that increasing phantom cells share of resource blocks decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. © 2016 IEEE.

  5. Resource allocation for phantom cellular networks: Energy efficiency vs spectral efficiency

    KAUST Repository

    Abdelhady, Amr M.

    2016-07-26

    Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Mean-while, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that finds the SE and EE resource allocation strategies for phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and phantom cells share of the total number of available resource blocks. We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It was found that increasing phantom cells share of resource blocks decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. © 2016 IEEE.

  6. Uncovering the footprints of malicious traffic in cellular data networks

    OpenAIRE

    Raghuramu, A; Zang, H; Chuah, CN

    2015-01-01

    © Springer International Publishing Switzerland 2015. In this paper, we present a comprehensive characterization of malicious traffic generated by mobile devices using Deep Packet Inspection (DPI) records and security event logs from a large US based cellular provider network. Our analysis reveals that 0.17% of mobile devices in the cellular network are affected by security threats. This proportion, while small, is orders of magnitude higher than the last reported (in 2013) infection rate of ...

  7. 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.

  8. 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.

  9. Signal-regulated systems and networks

    CSIR Research Space (South Africa)

    Van Zyl, TL

    2010-07-01

    Full Text Available The article presents the use of signal regulatory networks (SRNs), a biologically inspired model based on gene regulatory networks. SRNs are a way of understanding a class of self-organizing IT systems, signal-regulated systems (SRSs). This article...

  10. Capacity Enhancement of Uni‐directional In‐band Full‐Duplex Cellular Networks through Co‐channel Interference Cancellation

    Directory of Open Access Journals (Sweden)

    Hyungsik Ju

    2018-03-01

    Full Text Available As implementation of the in‐band full duplex (IFD transceiver becomes feasible, research interest is growing with respect to using IFD communication with cellular networks. However, the cellular network in which the IFD communication is applied inevitably suffers from an increase of the co‐channel interference (CCI due to IFD simultaneous transmission and reception. In this paper, we analyze the performance of a cellular network based on uni‐directional IFD (UD‐IFD communication, wherein an IFD base station simultaneously supports downlink and uplink transmissions of half‐duplex (HD users. In addition, a multi‐pair CCI cancellation (MP‐CCIC method combining CCIC and user pairing is proposed to improve the performance of the UD‐IFD network. Simulation results showed that, compared to a conventional HD cellular network without using CCIC, capacity gain was not obtained in the UD‐IFD cellular network. On the other hand, when applying the proposed MP‐CCIC, the capacity of the UD‐IFD cellular network greatly improved compared to that of an HD cellular network.

  11. Comparison of home and away-from-home physical activity using accelerometers and cellular network-based tracking devices.

    Science.gov (United States)

    Ramulu, Pradeep Y; Chan, Emilie S; Loyd, Tara L; Ferrucci, Luigi; Friedman, David S

    2012-08-01

    Measuring physical at home and away from home is essential for assessing health and well-being, and could help design interventions to increase physical activity. Here, we describe how physical activity at home and away from home can be quantified by combining information from cellular network-based tracking devices and accelerometers. Thirty-five working adults wore a cellular network-based tracking device and an accelerometer for 6 consecutive days and logged their travel away from home. Performance of the tracking device was determined using the travel log for reference. Tracking device and accelerometer data were merged to compare physical activity at home and away from home. The tracking device detected 98.6% of all away-from-home excursions, accurately measured time away from home and demonstrated few prolonged signal drop-out periods. Most physical activity took place away from home on weekdays, but not on weekends. Subjects were more physically active per unit of time while away from home, particularly on weekends. Cellular network-based tracking devices represent an alternative to global positioning systems for tracking location, and provide information easily integrated with accelerometers to determine where physical activity takes place. Promoting greater time spent away from home may increase physical activity.

  12. Dual-Level Game-Based Energy Efficiency and Fairness for Green Cellular Networks

    Directory of Open Access Journals (Sweden)

    Sungwook Kim

    2016-01-01

    Full Text Available In the recent decades, cellular networks have revolutionized the way of next generation communication networks. However, due to the global climate change, reducing the energy consumption of cellular infrastructures is an important and urgent problem. In this study, we propose a novel two-level cooperative game framework for improving the energy efficiency and fairness in cellular networks. For the energy efficiency, base stations (BSs constantly monitor the current traffic load and cooperate with each other to maximize the energy saving. For the energy fairness, renewable energy can be shared dynamically while ensuring the fairness among BSs. To achieve an excellent cellular network performance, the concepts of the Raiffa Bargaining Solution and Jain’s fairness are extended and practically applied to our dual-level cooperative game model. Through system level simulations, the proposed scheme is evaluated and compared with other existing schemes. The simulation results show that our two-level game approach outperforms the existing schemes in providing a better fair-efficient system performance.

  13. Spatiotemporal Stochastic Modeling of IoT Enabled Cellular Networks: Scalability and Stability Analysis

    KAUST Repository

    Gharbieh, Mohammad; Elsawy, Hesham; Bader, Ahmed; Alouini, Mohamed-Slim

    2017-01-01

    The Internet of Things (IoT) is large-scale by nature, which is manifested by the massive number of connected devices as well as their vast spatial existence. Cellular networks, which provide ubiquitous, reliable, and efficient wireless access, will play fundamental rule in delivering the first-mile access for the data tsunami to be generated by the IoT. However, cellular networks may have scalability problems to provide uplink connectivity to massive numbers of connected things. To characterize the scalability of cellular uplink in the context of IoT networks, this paper develops a traffic-aware spatiotemporal mathematical model for IoT devices supported by cellular uplink connectivity. The developed model is based on stochastic geometry and queueing theory to account for the traffic requirement per IoT device, the different transmission strategies, and the mutual interference between the IoT devices. To this end, the developed model is utilized to characterize the extent to which cellular networks can accommodate IoT traffic as well as to assess and compare three different transmission strategies that incorporate a combination of transmission persistency, backoff, and power-ramping. The analysis and the results clearly illustrate the scalability problem imposed by IoT on cellular network and offer insights into effective scenarios for each transmission strategy.

  14. Spatiotemporal Stochastic Modeling of IoT Enabled Cellular Networks: Scalability and Stability Analysis

    KAUST Repository

    Gharbieh, Mohammad

    2017-05-02

    The Internet of Things (IoT) is large-scale by nature, which is manifested by the massive number of connected devices as well as their vast spatial existence. Cellular networks, which provide ubiquitous, reliable, and efficient wireless access, will play fundamental rule in delivering the first-mile access for the data tsunami to be generated by the IoT. However, cellular networks may have scalability problems to provide uplink connectivity to massive numbers of connected things. To characterize the scalability of cellular uplink in the context of IoT networks, this paper develops a traffic-aware spatiotemporal mathematical model for IoT devices supported by cellular uplink connectivity. The developed model is based on stochastic geometry and queueing theory to account for the traffic requirement per IoT device, the different transmission strategies, and the mutual interference between the IoT devices. To this end, the developed model is utilized to characterize the extent to which cellular networks can accommodate IoT traffic as well as to assess and compare three different transmission strategies that incorporate a combination of transmission persistency, backoff, and power-ramping. The analysis and the results clearly illustrate the scalability problem imposed by IoT on cellular network and offer insights into effective scenarios for each transmission strategy.

  15. Image processing with a cellular nonlinear network

    International Nuclear Information System (INIS)

    Morfu, S.

    2005-01-01

    A cellular nonlinear network (CNN) based on uncoupled nonlinear oscillators is proposed for image processing purposes. It is shown theoretically and numerically that the contrast of an image loaded at the nodes of the CNN is strongly enhanced, even if this one is initially weak. An image inversion can be also obtained without reconfiguration of the network whereas a gray levels extraction can be performed with an additional threshold filtering. Lastly, an electronic implementation of this CNN is presented

  16. The cellular response to vascular endothelial growth factors requires co-ordinated signal transduction, trafficking and proteolysis.

    Science.gov (United States)

    Smith, Gina A; Fearnley, Gareth W; Tomlinson, Darren C; Harrison, Michael A; Ponnambalam, Sreenivasan

    2015-08-18

    VEGFs (vascular endothelial growth factors) are a family of conserved disulfide-linked soluble secretory glycoproteins found in higher eukaryotes. VEGFs mediate a wide range of responses in different tissues including metabolic homoeostasis, cell proliferation, migration and tubulogenesis. Such responses are initiated by VEGF binding to soluble and membrane-bound VEGFRs (VEGF receptor tyrosine kinases) and co-receptors. VEGF and receptor splice isoform diversity further enhances complexity of membrane protein assembly and function in signal transduction pathways that control multiple cellular responses. Different signal transduction pathways are simultaneously activated by VEGFR-VEGF complexes with membrane trafficking along the endosome-lysosome network further modulating signal output from multiple enzymatic events associated with such pathways. Balancing VEGFR-VEGF signal transduction with trafficking and proteolysis is essential in controlling the intensity and duration of different intracellular signalling events. Dysfunction in VEGF-regulated signal transduction is important in chronic disease states including cancer, atherosclerosis and blindness. This family of growth factors and receptors is an important model system for understanding human disease pathology and developing new therapeutics for treating such ailments. © 2015 Authors.

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

    Directory of Open Access Journals (Sweden)

    Kirouac Daniel C

    2012-05-01

    components through myriad alternate paths. Many of these paths are inconsistent with well-established mechanistic features of signalling networks, such as a requirement for a transmembrane receptor in sensing extracellular ligands. Conclusions Wide inconsistencies among interaction databases, pathway annotations, and the numbers and identities of nodes associated with a given pathway pose a major challenge for deriving causal and mechanistic insight from network graphs. We speculate that these inconsistencies are at least partially attributable to cell, and context-specificity of cellular signal transduction, which is largely unaccounted for in available databases, but the absence of standardized vocabularies is an additional confounding factor. As a result of discrepant annotations, it is very difficult to identify biologically meaningful pathways from interactome networks a priori. However, by incorporating prior knowledge, it is possible to successively build out network complexity with high confidence from a simple linear signal transduction scaffold. Such reduced complexity networks appear suitable for use in mechanistic models while being richer and better justified than the simple linear pathways usually depicted in diagrams of signal transduction.

  18. Collaborative multi-layer network coding for cellular cognitive radio networks

    KAUST Repository

    Sorour, Sameh

    2013-06-01

    In this paper, we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in underlay cellular cognitive radio networks. This scheme allows the collocated primary and cognitive radio base-stations to collaborate with each other, in order to minimize their own and each other\\'s packet recovery overheads, and thus improve their throughput, without any coordination between them. This non-coordinated collaboration is done using a novel multi-layer instantly decodable network coding scheme, which guarantees that each network\\'s help to the other network does not result in any degradation in its own performance. It also does not cause any violation to the primary networks interference thresholds in the same and adjacent cells. Yet, our proposed scheme both guarantees the reduction of the recovery overhead in collocated primary and cognitive radio networks, and allows early recovery of their packets compared to non-collaborative schemes. Simulation results show that a recovery overhead reduction of 15% and 40% can be achieved by our proposed scheme in the primary and cognitive radio networks, respectively, compared to the corresponding non-collaborative scheme. © 2013 IEEE.

  19. Information theory based approaches to cellular signaling.

    Science.gov (United States)

    Waltermann, Christian; Klipp, Edda

    2011-10-01

    Cells interact with their environment and they have to react adequately to internal and external changes such changes in nutrient composition, physical properties like temperature or osmolarity and other stresses. More specifically, they must be able to evaluate whether the external change is significant or just in the range of noise. Based on multiple external parameters they have to compute an optimal response. Cellular signaling pathways are considered as the major means of information perception and transmission in cells. Here, we review different attempts to quantify information processing on the level of individual cells. We refer to Shannon entropy, mutual information, and informal measures of signaling pathway cross-talk and specificity. Information theory in systems biology has been successfully applied to identification of optimal pathway structures, mutual information and entropy as system response in sensitivity analysis, and quantification of input and output information. While the study of information transmission within the framework of information theory in technical systems is an advanced field with high impact in engineering and telecommunication, its application to biological objects and processes is still restricted to specific fields such as neuroscience, structural and molecular biology. However, in systems biology dealing with a holistic understanding of biochemical systems and cellular signaling only recently a number of examples for the application of information theory have emerged. This article is part of a Special Issue entitled Systems Biology of Microorganisms. Copyright © 2011 Elsevier B.V. All rights reserved.

  20. Cognitive resource management for heterogeneous cellular networks

    CERN Document Server

    Liu, Yongkang

    2014-01-01

    This Springer Brief focuses on cognitive resource management in heterogeneous cellular networks (Het Net) with small cell deployment for the LTE-Advanced system. It introduces the Het Net features, presents practical approaches using cognitive radio technology in accommodating small cell data relay and optimizing resource allocation and examines the effectiveness of resource management among small cells given limited coordination bandwidth and wireless channel uncertainty. The authors introduce different network characteristics of small cell, investigate the mesh of small cell access points in

  1. Radio Channel Modelling for UAV Communication over Cellular Networks

    DEFF Research Database (Denmark)

    Amorim, Rafhael Medeiros de; Nguyen, Huan Cong; Mogensen, Preben Elgaard

    2017-01-01

    The main goal of this paper is to obtain models for path loss exponents and shadowing for the radio channel between airborne Unmanned Aerial Vehicles (UAVs) and cellular networks. In this pursuit, field measurements were conducted in live LTE networks at the 800 MHz frequency band, using a commer...

  2. Optimal Design of Gravitational Sewer Networks with General Cellular Automata

    Directory of Open Access Journals (Sweden)

    Mohammad Hadi Afshar

    2014-05-01

    Full Text Available In this paper, a Cellular Automata method is applied for the optimal design of sewer networks. The solution of sewer network optimization problems requires the determination of pipe diameters and average pipe cover depths, minimizing the total cost of the sewer network subject to operational constraints. In this paper, the network nodes and upstream and downstream pipe cover depths are considered as CA cells and cell states, respectively, and the links around each cell are taken into account as neighborhood. The proposed method is a general and flexible method for the optimization of sewer networks as it can be used to optimally design both gravity and pumped network due to the use of pipe nodal cover depths as the decision variables. The proposed method is tested against two  gravitational sewer networks and the  comparison of results with other methods such as  Genetic algorithm, Cellular Automata, Ant Colony Optimization Algorithm and Particle Swarm Optimization show the efficiency and effectiveness of the proposed method.

  3. Cellular observations enabled by microculture: paracrine signaling and population demographics†

    Science.gov (United States)

    Domenech, Maribella; Yu, Hongmei; Warrick, Jay; Badders, Nisha M.; Meyvantsson, Ivar; Alexander, Caroline M.; Beebe, David J.

    2009-01-01

    The cellular microenvironment plays a critical role in shaping and directing the process of communication between the cells. Soluble signals are responsible for many cellular behaviors such as cell survival, proliferation and differentiation. Despite the importance of soluble signals, canonical methods are not well suited to the study of soluble factor interactions between multiple cell types. Macro-scale technology often puts cells into a convective environment that can wash away and dilute soluble signals from their targets, minimizing local concentrations of important factors. In addition, current methods such as transwells, require large numbers of cells and are limited to studying just two cell types. Here, we present data supporting the use of microchannels to study soluble factor signaling providing improved sensitivity as well as the ability to move beyond existing co-culture and conditioned medium paradigms. In addition, we present data suggesting that microculture can be used to unmask effects of population demographics. In this example the data support the hypothesis that a growth promoting subpopulation of cells exists in the mouse mammary gland. PMID:20011455

  4. Cellular observations enabled by microculture: paracrine signaling and population demographics.

    Science.gov (United States)

    Domenech, Maribella; Yu, Hongmei; Warrick, Jay; Badders, Nisha M; Meyvantsson, Ivar; Alexander, Caroline M; Beebe, David J

    2009-03-01

    The cellular microenvironment plays a critical role in shaping and directing the process of communication between the cells. Soluble signals are responsible for many cellular behaviors such as cell survival, proliferation and differentiation. Despite the importance of soluble signals, canonical methods are not well suited to the study of soluble factor interactions between multiple cell types. Macro-scale technology often puts cells into a convective environment that can wash away and dilute soluble signals from their targets, minimizing local concentrations of important factors. In addition, current methods such as transwells, require large numbers of cells and are limited to studying just two cell types. Here, we present data supporting the use of microchannels to study soluble factor signaling providing improved sensitivity as well as the ability to move beyond existing co-culture and conditioned medium paradigms. In addition, we present data suggesting that microculture can be used to unmask effects of population demographics. In this example the data support the hypothesis that a growth promoting subpopulation of cells exists in the mouse mammary gland.

  5. Energy-Efficient Resource Allocation for Phantom Cellular Networks with Imperfect CSI

    KAUST Repository

    Abdelhady, Amr Mohamed Abdelaziz

    2017-03-28

    Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for a two-tier phantom cellular network, The optimization framework includes both EE and SE. We consider densely deployed phantom cellular networks and model the EE optimization problem taking into consideration the inevitable interference in this setup and imperfect channel estimation impairments. To this end, we propose three resource allocation strategies aiming at optimizing this network EE performance metric. Furthermore, we investigate the effect of changing some system parameters on the performance of these strategies, such as phantom cells resource units share, number of deployed phantom cells within a macro cell , number of pilots, and the phantom cells transmission power budget. It is found that increasing the number of pilots will deteriorate the EE performance of the whole setup, while increasing phantom cells transmission power budget will not affect the EE of the whole setup significantly. In addition, we observed that it is always useful to allocate most of the network resource units to the phantom cells tier.

  6. Energy-Efficient Resource Allocation for Phantom Cellular Networks with Imperfect CSI

    KAUST Repository

    Abdelhady, Amr Mohamed Abdelaziz; Amin, Osama; Alouini, Mohamed-Slim

    2017-01-01

    Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for a two-tier phantom cellular network, The optimization framework includes both EE and SE. We consider densely deployed phantom cellular networks and model the EE optimization problem taking into consideration the inevitable interference in this setup and imperfect channel estimation impairments. To this end, we propose three resource allocation strategies aiming at optimizing this network EE performance metric. Furthermore, we investigate the effect of changing some system parameters on the performance of these strategies, such as phantom cells resource units share, number of deployed phantom cells within a macro cell , number of pilots, and the phantom cells transmission power budget. It is found that increasing the number of pilots will deteriorate the EE performance of the whole setup, while increasing phantom cells transmission power budget will not affect the EE of the whole setup significantly. In addition, we observed that it is always useful to allocate most of the network resource units to the phantom cells tier.

  7. Extended LaSalle's Invariance Principle for Full-Range Cellular Neural Networks

    Directory of Open Access Journals (Sweden)

    Mauro Di Marco

    2009-01-01

    Full Text Available In several relevant applications to the solution of signal processing tasks in real time, a cellular neural network (CNN is required to be convergent, that is, each solution should tend toward some equilibrium point. The paper develops a Lyapunov method, which is based on a generalized version of LaSalle's invariance principle, for studying convergence and stability of the differential inclusions modeling the dynamics of the full-range (FR model of CNNs. The applicability of the method is demonstrated by obtaining a rigorous proof of convergence for symmetric FR-CNNs. The proof, which is a direct consequence of the fact that a symmetric FR-CNN admits a strict Lyapunov function, is much more simple than the corresponding proof of convergence for symmetric standard CNNs.

  8. Energy Efficient Resource Allocation for Phantom Cellular Networks

    KAUST Repository

    Abdelhady, Amr

    2016-04-01

    Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE. First, we consider sparsely deployed cells experiencing negligible interference and assume perfect channel state information (CSI). For this setting, we propose an algorithm that finds the SE and EE resource allocation strategies. Then, we compare the performance of both design strategies versus number of users, and phantom cells share of the total available resource units (RUs). We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It is found that increasing phantom cells share of RUs decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. Second, we consider the densely deployed phantom cellular networks and model the EE optimization problem having into consideration the inevitable interference and imperfect channel estimation. To this end, we propose three resource allocation strategies aiming at optimizing the EE performance metric of this network. Furthermore, we investigate the effect of changing some of the system parameters on the performance of the proposed strategies, such as phantom cells share of RUs, number of deployed phantom cells within a macro cell coverage, number of pilots and the maximum power available for transmission by the phantom cells BSs. It is found that increasing the number of pilots deteriorates the EE performance of the whole setup, while increasing maximum power available for phantom cells transmissions reduces the EE of the whole setup in a

  9. Hybrid Access Femtocells in Overlaid MIMO Cellular Networks with Transmit Selection under Poisson Field Interference

    KAUST Repository

    Abdel Nabi, Amr A

    2017-09-21

    This paper analyzes the performance of hybrid control-access schemes for small cells (such as femtocells) in the context of two-tier overlaid cellular networks. The proposed hybrid access schemes allow for sharing the same downlink resources between the small-cell network and the original macrocell network, and their mode of operations are characterized considering post-processed signal-to-interference-plus-noise ratios (SINRs) or pre-processed interference-aware operation. The work presents a detailed treatment of achieved performance of a desired user that benefits from MIMO arrays configuration through the use of transmit antenna selection (TAS) and maximal ratio combining (MRC) in the presence of Poisson field interference processes on spatial links. Furthermore, based on the interference awareness at the desired user, two TAS approaches are treated, which are the signal-to-noise (SNR)-based selection and SINR-based selection. The analysis is generalized to address the cases of highly-correlated and un-correlated aggregated interference on different transmit channels. In addition, the effect of delayed TAS due to imperfect feedback and the impact of arbitrary TAS processing are investigated. The analytical results are validated by simulations, to clarify some of the main outcomes herein.

  10. Hybrid Access Femtocells in Overlaid MIMO Cellular Networks with Transmit Selection under Poisson Field Interference

    KAUST Repository

    Abdel Nabi, Amr A; Al-Qahtani, Fawaz S.; Radaydeh, Redha Mahmoud Mesleh; Shaqfeh, Mohammed

    2017-01-01

    This paper analyzes the performance of hybrid control-access schemes for small cells (such as femtocells) in the context of two-tier overlaid cellular networks. The proposed hybrid access schemes allow for sharing the same downlink resources between the small-cell network and the original macrocell network, and their mode of operations are characterized considering post-processed signal-to-interference-plus-noise ratios (SINRs) or pre-processed interference-aware operation. The work presents a detailed treatment of achieved performance of a desired user that benefits from MIMO arrays configuration through the use of transmit antenna selection (TAS) and maximal ratio combining (MRC) in the presence of Poisson field interference processes on spatial links. Furthermore, based on the interference awareness at the desired user, two TAS approaches are treated, which are the signal-to-noise (SNR)-based selection and SINR-based selection. The analysis is generalized to address the cases of highly-correlated and un-correlated aggregated interference on different transmit channels. In addition, the effect of delayed TAS due to imperfect feedback and the impact of arbitrary TAS processing are investigated. The analytical results are validated by simulations, to clarify some of the main outcomes herein.

  11. Physical-layer Network Coding in Two-Way Heterogeneous Cellular Networks with Power Imbalance

    OpenAIRE

    Thampi, Ajay K; Liew, Soung Chang; Armour, Simon M D; Fan, Zhong; You, Lizhao; Kaleshi, Dritan

    2016-01-01

    The growing demand for high-speed data, quality of service (QoS) assurance and energy efficiency has triggered the evolution of 4G LTE-A networks to 5G and beyond. Interference is still a major performance bottleneck. This paper studies the application of physical-layer network coding (PNC), a technique that exploits interference, in heterogeneous cellular networks. In particular, we propose a rate-maximising relay selection algorithm for a single cell with multiple relays assuming the decode...

  12. Network reliability assessment using a cellular automata approach

    International Nuclear Information System (INIS)

    Rocco S, Claudio M.; Moreno, Jose Ali

    2002-01-01

    Two cellular automata (CA) models that evaluate the s-t connectedness and shortest path in a network are presented. CA based algorithms enhance the performance of classical algorithms, since they allow a more reliable and straightforward parallel implementation resulting in a dynamic network evaluation, where changes in the connectivity and/or link costs can readily be incorporated avoiding recalculation from scratch. The paper also demonstrates how these algorithms can be applied for network reliability evaluation (based on Monte-Carlo approach) and for finding s-t path with maximal reliability

  13. A Fluid Model for Performance Analysis in Cellular Networks

    Directory of Open Access Journals (Sweden)

    Coupechoux Marceau

    2010-01-01

    Full Text Available We propose a new framework to study the performance of cellular networks using a fluid model and we derive from this model analytical formulas for interference, outage probability, and spatial outage probability. The key idea of the fluid model is to consider the discrete base station (BS entities as a continuum of transmitters that are spatially distributed in the network. This model allows us to obtain simple analytical expressions to reveal main characteristics of the network. In this paper, we focus on the downlink other-cell interference factor (OCIF, which is defined for a given user as the ratio of its outer cell received power to its inner cell received power. A closed-form formula of the OCIF is provided in this paper. From this formula, we are able to obtain the global outage probability as well as the spatial outage probability, which depends on the location of a mobile station (MS initiating a new call. Our analytical results are compared to Monte Carlo simulations performed in a traditional hexagonal network. Furthermore, we demonstrate an application of the outage probability related to cell breathing and densification of cellular networks.

  14. Comparison of neural network applications for channel assignment in cellular TDMA networks and dynamically sectored PCS networks

    Science.gov (United States)

    Hortos, William S.

    1997-04-01

    The use of artificial neural networks (NNs) to address the channel assignment problem (CAP) for cellular time-division multiple access and code-division multiple access networks has previously been investigated by this author and many others. The investigations to date have been based on a hexagonal cell structure established by omnidirectional antennas at the base stations. No account was taken of the use of spatial isolation enabled by directional antennas to reduce interference between mobiles. Any reduction in interference translates into increased capacity and consequently alters the performance of the NNs. Previous studies have sought to improve the performance of Hopfield- Tank network algorithms and self-organizing feature map algorithms applied primarily to static channel assignment (SCA) for cellular networks that handle uniformly distributed, stationary traffic in each cell for a single type of service. The resulting algorithms minimize energy functions representing interference constraint and ad hoc conditions that promote convergence to optimal solutions. While the structures of the derived neural network algorithms (NNAs) offer the potential advantages of inherent parallelism and adaptability to changing system conditions, this potential has yet to be fulfilled the CAP for emerging mobile networks. The next-generation communication infrastructures must accommodate dynamic operating conditions. Macrocell topologies are being refined to microcells and picocells that can be dynamically sectored by adaptively controlled, directional antennas and programmable transceivers. These networks must support the time-varying demands for personal communication services (PCS) that simultaneously carry voice, data and video and, thus, require new dynamic channel assignment (DCA) algorithms. This paper examines the impact of dynamic cell sectoring and geometric conditioning on NNAs developed for SCA in omnicell networks with stationary traffic to improve the metrics

  15. Participatory sensing as an enabler for self-organisation in future cellular networks

    International Nuclear Information System (INIS)

    Imran, Muhammad Ali; Onireti, Oluwakayode; Imran, Ali

    2013-01-01

    In this short review paper we summarise the emerging challenges in the field of participatory sensing for the self-organisation of the next generation of wireless cellular networks. We identify the potential of participatory sensing in enabling the self-organisation, deployment optimisation and radio resource management of wireless cellular networks. We also highlight how this approach can meet the future goals for the next generation of cellular system in terms of infrastructure sharing, management of multiple radio access techniques, flexible usage of spectrum and efficient management of very small data cells

  16. Modeling of coupled differential equations for cellular chemical signaling pathways: Implications for assay protocols utilized in cellular engineering.

    Science.gov (United States)

    O'Clock, George D

    2016-08-01

    Cellular engineering involves modification and control of cell properties, and requires an understanding of fundamentals and mechanisms of action for cellular derived product development. One of the keys to success in cellular engineering involves the quality and validity of results obtained from cell chemical signaling pathway assays. The accuracy of the assay data cannot be verified or assured if the effect of positive feedback, nonlinearities, and interrelationships between cell chemical signaling pathway elements are not understood, modeled, and simulated. Nonlinearities and positive feedback in the cell chemical signaling pathway can produce significant aberrations in assay data collection. Simulating the pathway can reveal potential instability problems that will affect assay results. A simulation, using an electrical analog for the coupled differential equations representing each segment of the pathway, provides an excellent tool for assay validation purposes. With this approach, voltages represent pathway enzyme concentrations and operational amplifier feedback resistance and input resistance values determine pathway gain and rate constants. The understanding provided by pathway modeling and simulation is strategically important in order to establish experimental controls for assay protocol structure, time frames specified between assays, and assay concentration variation limits; to ensure accuracy and reproducibility of results.

  17. Instruction of hematopoietic lineage choice by cytokine signaling

    Energy Technology Data Exchange (ETDEWEB)

    Endele, Max; Etzrodt, Martin; Schroeder, Timm, E-mail: timm.schroeder@bsse.ethz.ch

    2014-12-10

    Hematopoiesis is the cumulative consequence of finely tuned signaling pathways activated through extrinsic factors, such as local niche signals and systemic hematopoietic cytokines. Whether extrinsic factors actively instruct the lineage choice of hematopoietic stem and progenitor cells or are only selectively allowing survival and proliferation of already intrinsically lineage-committed cells has been debated over decades. Recent results demonstrated that cytokines can instruct lineage choice. However, the precise function of individual cytokine-triggered signaling molecules in inducing cellular events like proliferation, lineage choice, and differentiation remains largely elusive. Signal transduction pathways activated by different cytokine receptors are highly overlapping, but support the production of distinct hematopoietic lineages. Cellular context, signaling dynamics, and the crosstalk of different signaling pathways determine the cellular response of a given extrinsic signal. New tools to manipulate and continuously quantify signaling events at the single cell level are therefore required to thoroughly interrogate how dynamic signaling networks yield a specific cellular response. - Highlights: • Recent studies provided definite proof for lineage-instructive action of cytokines. • Signaling pathways involved in hematopoietic lineage instruction remain elusive. • New tools are emerging to quantitatively study dynamic signaling networks over time.

  18. Dynamic spectrum management in green cognitive radio cellular networks

    KAUST Repository

    Sboui, Lokman

    2018-02-15

    In this paper, we propose a new cellular network operation scheme fulfilling the 5G requirements related to spectrum management and green communications. We focus on cognitive radio cellular networks in which both the primary network (PN) and the secondary network (SN) are maximizing their operational profits. The PN and the SN are required to respect a CO emissions threshold by switching off one or more lightly loaded base stations (BSs). In addition, the PN accepts to cooperate with the SN by leasing its spectrum in the cells where the PN is turned off. In return, the corresponding SN BSs host the PN users and impose extra roaming fees to the PN. We propose a low-complexity algorithm that maximizes the profit per CO emissions metric while switching on/off the BSs. In the simulations, we show that our proposed algorithm achieves performances close to the exhaustive search method. In addition, we find that the roaming price is a key parameter that affects both PN and SN profits.

  19. Network-Assisted Distributed Fairness-Aware Interference Coordination for Device-to-Device Communication Underlaid Cellular Networks

    Directory of Open Access Journals (Sweden)

    Francis Boabang

    2017-01-01

    Full Text Available Device-to-device (D2D communication underlaid cellular network is considered a key integration feature in future cellular network. However, without properly designed interference management, the interference from D2D transmission tends to degrade the performance of cellular users and D2D pairs. In this work, we proposed a network-assisted distributed interference mitigation scheme to address this issue. Specifically, the base station (BS acts as a control agent that coordinates the cross-tier interference from D2D transmission through a taxation scheme. The cotier interference is controlled by noncooperative game amongst D2D pairs. In general, the outcome of noncooperative game is inefficient due to the selfishness of each player. In our game formulation, reference user who is the victim of cotier interference is factored into the payoff function of each player to obtain fair and efficient outcome. The existence, uniqueness of the Nash Equilibrium (NE, and the convergence of the proposed algorithm are characterized using Variational Inequality theory. Finally, we provide simulation results to evaluate the efficiency of the proposed algorithm.

  20. A bead-based western for high-throughput cellular signal transduction analyses

    Science.gov (United States)

    Treindl, Fridolin; Ruprecht, Benjamin; Beiter, Yvonne; Schultz, Silke; Döttinger, Anette; Staebler, Annette; Joos, Thomas O.; Kling, Simon; Poetz, Oliver; Fehm, Tanja; Neubauer, Hans; Kuster, Bernhard; Templin, Markus F.

    2016-01-01

    Dissecting cellular signalling requires the analysis of large number of proteins. The DigiWest approach we describe here transfers the western blot to a bead-based microarray platform. By combining gel-based protein separation with immobilization on microspheres, hundreds of replicas of the initial blot are created, thus enabling the comprehensive analysis of limited material, such as cells collected by laser capture microdissection, and extending traditional western blotting to reach proteomic scales. The combination of molecular weight resolution, sensitivity and signal linearity on an automated platform enables the rapid quantification of hundreds of specific proteins and protein modifications in complex samples. This high-throughput western blot approach allowed us to identify and characterize alterations in cellular signal transduction that occur during the development of resistance to the kinase inhibitor Lapatinib, revealing major changes in the activation state of Ephrin-mediated signalling and a central role for p53-controlled processes. PMID:27659302

  1. QoE-Driven D2D Media Services Distribution Scheme in Cellular Networks

    Directory of Open Access Journals (Sweden)

    Mingkai Chen

    2017-01-01

    Full Text Available Device-to-device (D2D communication has been widely studied to improve network performance and considered as a potential technological component for the next generation communication. Considering the diverse users’ demand, Quality of Experience (QoE is recognized as a new degree of user’s satisfaction for media service transmissions in the wireless communication. Furthermore, we aim at promoting user’s Mean of Score (MOS value to quantify and analyze user’s QoE in the dynamic cellular networks. In this paper, we explore the heterogeneous media service distribution in D2D communications underlaying cellular networks to improve the total users’ QoE. We propose a novel media service scheme based on different QoE models that jointly solve the massive media content dissemination issue for cellular networks. Moreover, we also investigate the so-called Media Service Adaptive Update Scheme (MSAUS framework to maximize users’ QoE satisfaction and we derive the popularity and priority function of different media service QoE expression. Then, we further design Media Service Resource Allocation (MSRA algorithm to schedule limited cellular networks resource, which is based on the popularity function to optimize the total users’ QoE satisfaction and avoid D2D interference. In addition, numerical simulation results indicate that the proposed scheme is more effective in cellular network content delivery, which makes it suitable for various media service propagation.

  2. Analysis of Blocking Rate and Bandwidth Usage of Mobile IPTV Services in Wireless Cellular Networks

    Directory of Open Access Journals (Sweden)

    Mingfu Li

    2014-01-01

    Full Text Available Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes.

  3. Analysis of blocking rate and bandwidth usage of mobile IPTV services in wireless cellular networks.

    Science.gov (United States)

    Li, Mingfu

    2014-01-01

    Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes.

  4. Cellular neural networks for the stereo matching problem

    International Nuclear Information System (INIS)

    Taraglio, S.; Zanela, A.

    1997-03-01

    The applicability of the Cellular Neural Network (CNN) paradigm to the problem of recovering information on the tridimensional structure of the environment is investigated. The approach proposed is the stereo matching of video images. The starting point of this work is the Zhou-Chellappa neural network implementation for the same problem. The CNN based system we present here yields the same results as the previous approach, but without the many existing drawbacks

  5. Channel Access and Power Control for Mobile Crowdsourcing in Device-to-Device Underlaid Cellular Networks

    Directory of Open Access Journals (Sweden)

    Yue Ma

    2018-01-01

    Full Text Available With the access of a myriad of smart handheld devices in cellular networks, mobile crowdsourcing becomes increasingly popular, which can leverage omnipresent mobile devices to promote the complicated crowdsourcing tasks. Device-to-device (D2D communication is highly desired in mobile crowdsourcing when cellular communications are costly. The D2D cellular network is more preferable for mobile crowdsourcing than conventional cellular network. Therefore, this paper addresses the channel access and power control problem in the D2D underlaid cellular networks. We propose a novel semidistributed network-assisted power and a channel access control scheme for D2D user equipment (DUE pieces. It can control the interference from DUE pieces to the cellular user accurately and has low information feedback overhead. For the proposed scheme, the stochastic geometry tool is employed and analytic expressions are derived for the coverage probabilities of both the cellular link and D2D links. We analyze the impact of key system parameters on the proposed scheme. The Pareto optimal access threshold maximizing the total area spectral efficiency is obtained. Unlike the existing works, the performances of the cellular link and D2D links are both considered. Simulation results show that the proposed method can improve the total area spectral efficiency significantly compared to existing schemes.

  6. Multi-Hop Link Capacity of Multi-Route Multi-Hop MRC Diversity for a Virtual Cellular Network

    Science.gov (United States)

    Daou, Imane; Kudoh, Eisuke; Adachi, Fumiyuki

    In virtual cellular network (VCN), proposed for high-speed mobile communications, the signal transmitted from a mobile terminal is received by some wireless ports distributed in each virtual cell and relayed to the central port that acts as a gateway to the core network. In this paper, we apply the multi-route MHMRC diversity in order to decrease the transmit power and increase the multi-hop link capacity. The transmit power, the interference power and the link capacity are evaluated for DS-CDMA multi-hop VCN by computer simulation. The multi-route MHMRC diversity can be applied to not only DS-CDMA but also other access schemes (i. e. MC-CDMA, OFDM, etc.).

  7. Wireless traffic steering for green cellular networks

    CERN Document Server

    Zhang, Shan; Zhou, Sheng; Niu, Zhisheng; Shen, Xuemin (Sherman)

    2016-01-01

    This book introduces wireless traffic steering as a paradigm to realize green communication in multi-tier heterogeneous cellular networks. By matching network resources and dynamic mobile traffic demand, traffic steering helps to reduce on-grid power consumption with on-demand services provided. This book reviews existing solutions from the perspectives of energy consumption reduction and renewable energy harvesting. Specifically, it explains how traffic steering can improve energy efficiency through intelligent traffic-resource matching. Several promising traffic steering approaches for dynamic network planning and renewable energy demand-supply balancing are discussed. This book presents an energy-aware traffic steering method for networks with energy harvesting, which optimizes the traffic allocated to each cell based on the renewable energy status. Renewable energy demand-supply balancing is a key factor in energy dynamics, aimed at enhancing renewable energy sustainability to reduce on-grid energy consum...

  8. Collaborative Multi-Layer Network Coding in Hybrid Cellular Cognitive Radio Networks

    KAUST Repository

    Moubayed, Abdallah J.

    2015-05-01

    In this paper, as an extension to [1], we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in hybrid (interweave and underlay) cellular cognitive radio networks. This scheme allows the uncoordinated collaboration between the collocated primary and cognitive radio base-stations in order to minimize their own as well as each other\\'s packet recovery overheads, thus by improving their throughput. The proposed scheme ensures that each network\\'s performance is not degraded by its help to the other network. Moreover, it guarantees that the primary network\\'s interference threshold is not violated in the same and adjacent cells. Yet, the scheme allows the reduction of the recovery overhead in the collocated primary and cognitive radio networks. The reduction in the cognitive radio network is further amplified due to the perfect detection of spectrum holes which allows the cognitive radio base station to transmit at higher power without fear of violating the interference threshold of the primary network. For the secondary network, simulation results show reductions of 20% and 34% in the packet recovery overhead, compared to the non-collaborative scheme, for low and high probabilities of primary packet arrivals, respectively. For the primary network, this reduction was found to be 12%. © 2015 IEEE.

  9. Detection of silent cells, synchronization and modulatory activity in developing cellular networks.

    Science.gov (United States)

    Hjorth, Johannes J J; Dawitz, Julia; Kroon, Tim; Pires, Johny; Dassen, Valerie J; Berkhout, Janna A; Emperador Melero, Javier; Nadadhur, Aish G; Alevra, Mihai; Toonen, Ruud F; Heine, Vivi M; Mansvelder, Huibert D; Meredith, Rhiannon M

    2016-04-01

    Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell migration, to the refinement of synapses, topographic maps, and the mature composition of ion channels. These emergent activity patterns are not present in all cells simultaneously within the network and more immature "silent" cells, potentially correlated with the presence of silent synapses, are prominent in different networks during early developmental periods. Many current network analyses for detection of synchronous cellular activity utilize activity-based pixel correlations to identify cellular-based regions of interest (ROIs) and coincident cell activity. However, using activity-based correlations, these methods first underestimate or ignore the inactive silent cells within the developing network and second, are difficult to apply within cell-dense regions commonly found in developing brain networks. In addition, previous methods may ignore ROIs within a network that shows transient activity patterns comprising both inactive and active periods. We developed analysis software to semi-automatically detect cells within developing neuronal networks that were imaged using calcium-sensitive reporter dyes. Using an iterative threshold, modulation of activity was tracked within individual cells across the network. The distribution pattern of both inactive and active, including synchronous cells, could be determined based on distance measures to neighboring cells and according to different anatomical layers. © 2015 Wiley Periodicals, Inc.

  10. Energy Cost Minimization in Heterogeneous Cellular Networks with Hybrid Energy Supplies

    Directory of Open Access Journals (Sweden)

    Bang Wang

    2016-01-01

    Full Text Available The ever increasing data demand has led to the significant increase of energy consumption in cellular mobile networks. Recent advancements in heterogeneous cellular networks and green energy supplied base stations provide promising solutions for cellular communications industry. In this article, we first review the motivations and challenges as well as approaches to address the energy cost minimization problem for such green heterogeneous networks. Owing to the diversities of mobile traffic and renewable energy, the energy cost minimization problem involves both temporal and spatial optimization of resource allocation. We next present a new solution to illustrate how to combine the optimization of the temporal green energy allocation and spatial mobile traffic distribution. The whole optimization problem is decomposed into four subproblems, and correspondingly our proposed solution is divided into four parts: energy consumption estimation, green energy allocation, user association, and green energy reallocation. Simulation results demonstrate that our proposed algorithm can significantly reduce the total energy cost.

  11. Optimized Energy Procurement for Cellular Networks with Uncertain Renewable Energy Generation

    KAUST Repository

    Rached, Nadhir B.

    2017-02-07

    Renewable energy (RE) is an emerging solution for reducing carbon dioxide (CO2) emissions from cellular networks. One of the challenges of using RE sources is to handle its inherent uncertainty. In this paper, a RE powered cellular network is investigated. For a one-day operation cycle, the cellular network aims to reduce energy procurement costs from the smart grid by optimizing the amounts of energy procured from their locally deployed RE sources as well as from the smart grid. In addition to that, it aims to determine the extra amount of energy to be sold to the electrical grid at each time period. Chance constrained optimization is first proposed to deal with the randomness in the RE generation. Then, to make the optimization problem tractable, two well- know convex approximation methods, namely; Chernoff and Chebyshev based-approaches, are analyzed in details. Numerical results investigate the optimized energy procurement for various daily scenarios and compare between the performances of the employed convex approximation approaches.

  12. Organization of signal flow in directed networks

    International Nuclear Information System (INIS)

    Bányai, M; Bazsó, F; Négyessy, L

    2011-01-01

    Confining an answer to the question of whether and how the coherent operation of network elements is determined by the network structure is the topic of our work. We map the structure of signal flow in directed networks by analysing the degree of edge convergence and the overlap between the in- and output sets of an edge. Definitions of convergence degree and overlap are based on the shortest paths, thus they encapsulate global network properties. Using the defining notions of convergence degree and overlapping set we clarify the meaning of network causality and demonstrate the crucial role of chordless circles. In real-world networks the flow representation distinguishes nodes according to their signal transmitting, processing and control properties. The analysis of real-world networks in terms of flow representation was in accordance with the known functional properties of the network nodes. It is shown that nodes with different signal processing, transmitting and control properties are randomly connected at the global scale, while local connectivity patterns depart from randomness. The grouping of network nodes according to their signal flow properties was unrelated to the network's community structure. We present evidence that the signal flow properties of small-world-like, real-world networks cannot be reconstructed by algorithms used to generate small-world networks. Convergence degree values were calculated for regular oriented trees, and the probability density function for networks grown with the preferential attachment mechanism. For Erdos–Rényi graphs we calculated the probability density function of both convergence degrees and overlaps

  13. On Optimal Geographical Caching in Heterogeneous Cellular Networks

    NARCIS (Netherlands)

    Serbetci, Berksan; Goseling, Jasper

    2017-01-01

    In this work we investigate optimal geographical caching in heterogeneous cellular networks where different types of base stations (BSs) have different cache capacities. Users request files from a content library according to a known probability distribution. The performance metric is the total hit

  14. Discovery of nitrate-CPK-NLP signalling in central nutrient-growth networks

    Science.gov (United States)

    Liu, Kun-hsiang; Niu, Yajie; Konishi, Mineko; Wu, Yue; Du, Hao; Sun Chung, Hoo; Li, Lei; Boudsocq, Marie; McCormack, Matthew; Maekawa, Shugo; Ishida, Tetsuya; Zhang, Chao; Shokat, Kevan; Yanagisawa, Shuichi; Sheen, Jen

    2018-01-01

    Nutrient signalling integrates and coordinates gene expression, metabolism and growth. However, its primary molecular mechanisms remain incompletely understood in plants and animals. Here we report novel Ca2+ signalling triggered by nitrate with live imaging of an ultrasensitive biosensor in Arabidopsis leaves and roots. A nitrate-sensitized and targeted functional genomic screen identifies subgroup III Ca2+-sensor protein kinases (CPKs) as master regulators orchestrating primary nitrate responses. A chemical switch with the engineered CPK10(M141G) kinase enables conditional analyses of cpk10,30,32 to define comprehensive nitrate-associated regulatory and developmental programs, circumventing embryo lethality. Nitrate-CPK signalling phosphorylates conserved NIN-LIKE PROTEIN (NLP) transcription factors (TFs) to specify reprogramming of gene sets for downstream TFs, transporters, N-assimilation, C/N-metabolism, redox, signalling, hormones, and proliferation. Conditional cpk10,30,32 and nlp7 similarly impair nitrate-stimulated system-wide shoot growth and root establishment. The nutrient-coupled Ca2+ signalling network integrates transcriptome and cellular metabolism with shoot-root coordination and developmental plasticity in shaping organ biomass and architecture. PMID:28489820

  15. Multi-operator collaboration for green cellular networks under roaming price consideration

    KAUST Repository

    Ghazzai, Hakim; Yaacoub, Elias E.; Alouini, Mohamed-Slim

    2014-01-01

    This paper investigates the collaboration between multiple mobile operators to optimize the energy efficiency of cellular networks. Our framework studies the case of LTE-Advanced networks deployed in the same area and owning renewable energy generators. The objective is to reduce the CO2 emissions of cellular networks via collaborative techniques and using base station sleeping strategy while respecting the network quality of service. Low complexity and practical algorithm is employed to achieve green goals during low traffic periods. Cooperation decision criteria are also established basing on derived roaming prices and profit gains of competitive mobile operators. Our numerical results show a significant save in terms of CO2 compared to the non-collaboration case and that cooperative mobile operator exploiting renewables are more awarded than traditional operators.

  16. Multi-operator collaboration for green cellular networks under roaming price consideration

    KAUST Repository

    Ghazzai, Hakim

    2014-09-01

    This paper investigates the collaboration between multiple mobile operators to optimize the energy efficiency of cellular networks. Our framework studies the case of LTE-Advanced networks deployed in the same area and owning renewable energy generators. The objective is to reduce the CO2 emissions of cellular networks via collaborative techniques and using base station sleeping strategy while respecting the network quality of service. Low complexity and practical algorithm is employed to achieve green goals during low traffic periods. Cooperation decision criteria are also established basing on derived roaming prices and profit gains of competitive mobile operators. Our numerical results show a significant save in terms of CO2 compared to the non-collaboration case and that cooperative mobile operator exploiting renewables are more awarded than traditional operators.

  17. Information theory and signal transduction systems: from molecular information processing to network inference.

    Science.gov (United States)

    Mc Mahon, Siobhan S; Sim, Aaron; Filippi, Sarah; Johnson, Robert; Liepe, Juliane; Smith, Dominic; Stumpf, Michael P H

    2014-11-01

    Sensing and responding to the environment are two essential functions that all biological organisms need to master for survival and successful reproduction. Developmental processes are marshalled by a diverse set of signalling and control systems, ranging from systems with simple chemical inputs and outputs to complex molecular and cellular networks with non-linear dynamics. Information theory provides a powerful and convenient framework in which such systems can be studied; but it also provides the means to reconstruct the structure and dynamics of molecular interaction networks underlying physiological and developmental processes. Here we supply a brief description of its basic concepts and introduce some useful tools for systems and developmental biologists. Along with a brief but thorough theoretical primer, we demonstrate the wide applicability and biological application-specific nuances by way of different illustrative vignettes. In particular, we focus on the characterisation of biological information processing efficiency, examining cell-fate decision making processes, gene regulatory network reconstruction, and efficient signal transduction experimental design. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Velocity-Aware Handover Management in Two-Tier Cellular Networks

    KAUST Repository

    Arshad, Rabe

    2017-01-19

    While network densification is considered an important solution to cater the ever-increasing capacity demand, its effect on the handover (HO) rate is overlooked. In dense 5G networks, HO delays may neutralize or even negate the gains offered by network densification. Hence, user mobility imposes a nontrivial challenge to harvest capacity gains via network densification. In this paper, we propose a velocity-aware HO management scheme for two-tier downlink cellular network to mitigate the HO effect on the foreseen densification throughput gains. The proposed HO scheme sacrifices the best base station (BS) connectivity, by skipping HO to some BSs along the user trajectory, to maintain longer connection durations and reduce HO rates. Furthermore, the proposed scheme enables cooperative BS service and strongest interference cancellation to compensate for skipping the best connectivity. To this end, we consider different HO skipping scenarios and develop a velocity-aware mathematical model, via stochastic geometry, to quantify the performance of the proposed HO schemes in terms of the coverage probability and user throughput. The results highlight the HO rate problem in dense cellular environments and show the importance of the proposed HO schemes. Finally, the value of BS cooperation along with handover skipping is quantified for different user mobility profiles.

  19. Load-aware modeling for uplink cellular networks in a multi-channel environment

    KAUST Repository

    AlAmmouri, Ahmad

    2014-09-01

    We exploit tools from stochastic geometry to develop a tractable analytical approach for modeling uplink cellular networks. The developed model is load aware and accounts for per-user power control as well as the limited transmit power constraint for the users\\' equipment (UEs). The proposed analytical paradigm is based on a simple per-user power control scheme in which each user inverts his path-loss such that the signal is received at his serving base station (BS) with a certain power threshold ρ Due to the limited transmit power of the UEs, users that cannot invert their path-loss to their serving BSs are allowed to transmit with their maximum transmit power. We show that the proposed power control scheme not only provides a balanced cell center and cell edge user performance, it also facilitates the analysis when compared to the state-of-the-art approaches in the literature. To this end, we discuss how to manipulate the design variable ρ in response to the network parameters to optimize one or more of the performance metrics such as the outage probability, the network capacity, and the energy efficiency.

  20. Best response game of traffic on road network of non-signalized intersections

    Science.gov (United States)

    Yao, Wang; Jia, Ning; Zhong, Shiquan; Li, Liying

    2018-01-01

    This paper studies the traffic flow in a grid road network with non-signalized intersections. The nature of the drivers in the network is simulated such that they play an iterative snowdrift game with other drivers. A cellular automata model is applied to study the characteristics of the traffic flow and the evolution of the behaviour of the drivers during the game. The drivers use best-response as their strategy to update rules. Three major findings are revealed. First, the cooperation rate in simulation experiences staircase-shaped drop as cost to benefit ratio r increases, and cooperation rate can be derived analytically as a function of cost to benefit ratio r. Second, we find that higher cooperation rate corresponds to higher average speed, lower density and higher flow. This reveals that defectors deteriorate the efficiency of traffic on non-signalized intersections. Third, the system experiences more randomness when the density is low because the drivers will not have much opportunity to update strategy when the density is low. These findings help to show how the strategy of drivers in a traffic network evolves and how their interactions influence the overall performance of the traffic system.

  1. Power Control for D2D Underlay Cellular Networks With Channel Uncertainty

    KAUST Repository

    Memmi, Amen; Rezki, Zouheir; Alouini, Mohamed-Slim

    2016-01-01

    Device-to-device (D2D) communications underlying the cellular infrastructure are a technology that have been proposed recently as a promising solution to enhance cellular network capabilities. It improves spectrum utilization, overall throughput

  2. Stability analysis for cellular neural networks with variable delays

    International Nuclear Information System (INIS)

    Zhang Qiang; Wei Xiaopeng; Xu Jin

    2006-01-01

    Some sufficient conditions for the global exponential stability of cellular neural networks with variable delay are obtained by means of a method based on delay differential inequality. The method, which does not make use of Lyapunov functionals, is simple and effective for the stability analysis of neural networks with delay. Some previously established results in the literature are shown to be special cases of the presented result

  3. 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

  4. Semantic Mining based on graph theory and ontologies. Case Study: Cell Signaling Pathways

    Directory of Open Access Journals (Sweden)

    Carlos R. Rangel

    2016-08-01

    Full Text Available In this paper we use concepts from graph theory and cellular biology represented as ontologies, to carry out semantic mining tasks on signaling pathway networks. Specifically, the paper describes the semantic enrichment of signaling pathway networks. A cell signaling network describes the basic cellular activities and their interactions. The main contribution of this paper is in the signaling pathway research area, it proposes a new technique to analyze and understand how changes in these networks may affect the transmission and flow of information, which produce diseases such as cancer and diabetes. Our approach is based on three concepts from graph theory (modularity, clustering and centrality frequently used on social networks analysis. Our approach consists into two phases: the first uses the graph theory concepts to determine the cellular groups in the network, which we will call them communities; the second uses ontologies for the semantic enrichment of the cellular communities. The measures used from the graph theory allow us to determine the set of cells that are close (for example, in a disease, and the main cells in each community. We analyze our approach in two cases: TGF-ß and the Alzheimer Disease.

  5. Network modeling reveals prevalent negative regulatory relationships between signaling sectors in Arabidopsis immune signaling.

    Directory of Open Access Journals (Sweden)

    Masanao Sato

    Full Text Available Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. We studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2. This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles for 571 immune response genes of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with Pto DC3000 AvrRpt2. The mRNA profiles were analyzed as detailed descriptions of changes in the network state resulting from the genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting static network model accurately predicted 23 of 25 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i the components of the network are highly interconnected; and (ii negative regulatory relationships are common between signaling sectors. Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a "sector

  6. Nuclear and cytoplasmic signalling in the cellular response to ionising radiation

    International Nuclear Information System (INIS)

    Szumiel, Irena

    2001-01-01

    DNA is the universal primary target for ionising radiation; however, the cellular response is highly diversified not only by differential DNA repair ability. The monitoring system for the ionising radiation-inflicted DNA damage consists of 3 apparently independently acting enzymes which are activated by DNA breaks: two protein kinases, ATM (ataxia telangiectasia mutated) and DNA-PK (DNA-dependent protein kinase) and a poly(ADP-ribose) polymerase, PARP-1. These 3 enzymes are the source of alarm signals, which affect to various extents DNA repair, progression through the cell cycle and eventually the pathway to cell death. Their functions probably are partly overlapping. On the side of DNA repair their role consists in recruiting and/or activating the repair enzymes, as well as preventing illegitimate recombination of the damaged sites. A large part of the nuclear signalling pathway, including the integrating role of TP53 has been revealed. Two main signalling pathways start at the plasma membrane: the MAPK/ERK (mitogen and extracellular signal regulated protein kinase family) 'survival pathway' and the SAPK/JNK (stress-activated protein kinase/c-Jun N-terminal kinase) 'cell death pathway'. The balance between them is likely to determine the cell's fate. An additional important 'survival pathway' starts at the insulin-like growth factor type I receptor (IGF-IR), involves phosphoinositide- 3 kinase and Akt kinase and is targeted at inactivation of the pro-apoptotic BAD protein. Interestingly, over-expression of IGF-IR almost entirely abrogates the extreme radiation sensitivity of ataxia telangiectasia cells. When DNA break rejoining is impaired, the cell is unconditionally radiation sensitive. The fate of a repair-competent cell is determined by the time factor: the cell cycle arrest should be long enough to ensure the completion of repair. Incomplete repair or misrepair may be tolerated, when generation of the death signal is prevented. So, the character and timing

  7. A Biologically-Inspired Power Control Algorithm for Energy-Efficient Cellular Networks

    Directory of Open Access Journals (Sweden)

    Hyun-Ho Choi

    2016-03-01

    Full Text Available Most of the energy used to operate a cellular network is consumed by a base station (BS, and reducing the transmission power of a BS can therefore afford a substantial reduction in the amount of energy used in a network. In this paper, we propose a distributed transmit power control (TPC algorithm inspired by bird flocking behavior as a means of improving the energy efficiency of a cellular network. Just as each bird in a flock attempts to match its velocity with the average velocity of adjacent birds, in the proposed algorithm, each mobile station (MS in a cell matches its rate with the average rate of the co-channel MSs in adjacent cells by controlling the transmit power of its serving BS. We verify that this bio-inspired TPC algorithm using a local rate-average process achieves an exponential convergence and maximizes the minimum rate of the MSs concerned. Simulation results show that the proposed TPC algorithm follows the same convergence properties as the flocking algorithm and also effectively reduces the power consumption at the BSs while maintaining a low outage probability as the inter-cell interference increases; in so doing, it significantly improves the energy efficiency of a cellular network.

  8. Social multimedia signals a signal processing approach to social network phenomena

    CERN Document Server

    Roy, Suman Deb

    2014-01-01

    This book provides a comprehensive coverage of the state-of-the-art in understanding media popularity and trends in online social networks through social multimedia signals. With insights from the study of popularity and sharing patterns of online media, trend spread in social media, social network analysis for multimedia and visualizing diffusion of media in online social networks. In particular, the book will address the following important issues: Understanding social network phenomena from a signal processing point of view; The existence and popularity of multimedia as shared and social me

  9. Hypoxia induces a phase transition within a kinase signaling network in cancer cells

    Science.gov (United States)

    Wei, Wei; Shi, Qihui; Remacle, Francoise; Qin, Lidong; Shackelford, David B.; Shin, Young Shik; Mischel, Paul S.; Levine, R. D.; Heath, James R.

    2013-01-01

    Hypoxia is a near-universal feature of cancer, promoting glycolysis, cellular proliferation, and angiogenesis. The molecular mechanisms of hypoxic signaling have been intensively studied, but the impact of changes in oxygen partial pressure (pO2) on the state of signaling networks is less clear. In a glioblastoma multiforme (GBM) cancer cell model, we examined the response of signaling networks to targeted pathway inhibition between 21% and 1% pO2. We used a microchip technology that facilitates quantification of a panel of functional proteins from statistical numbers of single cells. We find that near 1.5% pO2, the signaling network associated with mammalian target of rapamycin (mTOR) complex 1 (mTORC1)—a critical component of hypoxic signaling and a compelling cancer drug target—is deregulated in a manner such that it will be unresponsive to mTOR kinase inhibitors near 1.5% pO2, but will respond at higher or lower pO2 values. These predictions were validated through experiments on bulk GBM cell line cultures and on neurosphere cultures of a human-origin GBM xenograft tumor. We attempt to understand this behavior through the use of a quantitative version of Le Chatelier’s principle, as well as through a steady-state kinetic model of protein interactions, both of which indicate that hypoxia can influence mTORC1 signaling as a switch. The Le Chatelier approach also indicates that this switch may be thought of as a type of phase transition. Our analysis indicates that certain biologically complex cell behaviors may be understood using fundamental, thermodynamics-motivated principles. PMID:23530221

  10. Hypoxia induces a phase transition within a kinase signaling network in cancer cells.

    Science.gov (United States)

    Wei, Wei; Shi, Qihui; Remacle, Francoise; Qin, Lidong; Shackelford, David B; Shin, Young Shik; Mischel, Paul S; Levine, R D; Heath, James R

    2013-04-09

    Hypoxia is a near-universal feature of cancer, promoting glycolysis, cellular proliferation, and angiogenesis. The molecular mechanisms of hypoxic signaling have been intensively studied, but the impact of changes in oxygen partial pressure (pO2) on the state of signaling networks is less clear. In a glioblastoma multiforme (GBM) cancer cell model, we examined the response of signaling networks to targeted pathway inhibition between 21% and 1% pO2. We used a microchip technology that facilitates quantification of a panel of functional proteins from statistical numbers of single cells. We find that near 1.5% pO2, the signaling network associated with mammalian target of rapamycin (mTOR) complex 1 (mTORC1)--a critical component of hypoxic signaling and a compelling cancer drug target--is deregulated in a manner such that it will be unresponsive to mTOR kinase inhibitors near 1.5% pO2, but will respond at higher or lower pO2 values. These predictions were validated through experiments on bulk GBM cell line cultures and on neurosphere cultures of a human-origin GBM xenograft tumor. We attempt to understand this behavior through the use of a quantitative version of Le Chatelier's principle, as well as through a steady-state kinetic model of protein interactions, both of which indicate that hypoxia can influence mTORC1 signaling as a switch. The Le Chatelier approach also indicates that this switch may be thought of as a type of phase transition. Our analysis indicates that certain biologically complex cell behaviors may be understood using fundamental, thermodynamics-motivated principles.

  11. Analytical modeling of mode selection and power control for underlay D2D communication in cellular networks

    KAUST Repository

    Elsawy, Hesham

    2014-11-01

    Device-to-device (D2D) communication enables the user equipments (UEs) located in close proximity to bypass the cellular base stations (BSs) and directly connect to each other, and thereby, offload traffic from the cellular infrastructure. D2D communication can improve spatial frequency reuse and energy efficiency in cellular networks. This paper presents a comprehensive and tractable analytical framework for D2D-enabled uplink cellular networks with a flexible mode selection scheme along with truncated channel inversion power control. The developed framework is used to analyze and understand how the underlaying D2D communication affects the cellular network performance. Through comprehensive numerical analysis, we investigate the expected performance gains and provide guidelines for selecting the network parameters.

  12. Global Optimization for Transport Network Expansion and Signal Setting

    OpenAIRE

    Liu, Haoxiang; Wang, David Z. W.; Yue, Hao

    2015-01-01

    This paper proposes a model to address an urban transport planning problem involving combined network design and signal setting in a saturated network. Conventional transport planning models usually deal with the network design problem and signal setting problem separately. However, the fact that network capacity design and capacity allocation determined by network signal setting combine to govern the transport network performance requires the optimal transport planning to consider the two pr...

  13. Global exponential stability for nonautonomous cellular neural networks with delays

    International Nuclear Information System (INIS)

    Zhang Qiang; Wei Xiaopeng; Xu Jin

    2006-01-01

    In this Letter, by utilizing Lyapunov functional method and Halanay inequalities, we analyze global exponential stability of nonautonomous cellular neural networks with delay. Several new sufficient conditions ensuring global exponential stability of the network are obtained. The results given here extend and improve the earlier publications. An example is given to demonstrate the effectiveness of the obtained results

  14. Fundamental Tradeoffs among Reliability, Latency and Throughput in Cellular Networks

    DEFF Research Database (Denmark)

    Soret, Beatriz; Mogensen, Preben; Pedersen, Klaus I.

    2014-01-01

    We address the fundamental tradeoffs among latency, reliability and throughput in a cellular network. The most important elements influencing the KPIs in a 4G network are identified, and the inter-relationships among them is discussed. We use the effective bandwidth and the effective capacity......, in which latency and reliability will be two of the principal KPIs....

  15. Distributed Velocity-Dependent Protocol for Multihop Cellular Sensor Networks

    Directory of Open Access Journals (Sweden)

    Deepthi Chander

    2009-01-01

    Full Text Available Cell phones are embedded with sensors form a Cellular Sensor Network which can be used to localize a moving event. The inherent mobility of the application and of the cell phone users warrants distributed structure-free data aggregation and on-the-fly routing. We propose a Distributed Velocity-Dependent (DVD protocol to localize a moving event using a Multihop Cellular Sensor Network (MCSN. DVD is based on a novel form of connectivity determined by the waiting time of nodes for a Random Waypoint (RWP distribution of cell phone users. This paper analyzes the time-stationary and spatial distribution of the proposed waiting time to explain the superior event localization and delay performances of DVD over the existing Randomized Waiting (RW protocol. A sensitivity analysis is also performed to compare the performance of DVD with RW and the existing Centralized approach.

  16. Optimized Energy Efficiency and Spectral Efficiency Resource Allocation Strategies for Phantom Cellular Networks

    KAUST Repository

    Abdelhady, Amr, M.; Amin, Osama; Alouini, Mohamed-Slim

    2016-01-01

    Multi-teir hetrogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-teir architecture known as Phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that computes the SE and EE resource allocation for Phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and the ration of Phantom cellresource blocks to the total number or resource blocks. We aim to investigate the effect of some system parameters to acheive improved SE or EE performance at a non-significant loss in EE or SE performance, respectively. It was found that the system parameters can be tuned so that the EE solution does not yield a significant loss in the SE performance.

  17. Optimized Energy Efficiency and Spectral Efficiency Resource Allocation Strategies for Phantom Cellular Networks

    KAUST Repository

    Abdelhady, Amr, M.

    2016-01-06

    Multi-teir hetrogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-teir architecture known as Phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that computes the SE and EE resource allocation for Phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and the ration of Phantom cellresource blocks to the total number or resource blocks. We aim to investigate the effect of some system parameters to acheive improved SE or EE performance at a non-significant loss in EE or SE performance, respectively. It was found that the system parameters can be tuned so that the EE solution does not yield a significant loss in the SE performance.

  18. Ebola virus modulates transforming growth factor β signaling and cellular markers of mesenchyme-like transition in hepatocytes.

    Science.gov (United States)

    Kindrachuk, Jason; Wahl-Jensen, Victoria; Safronetz, David; Trost, Brett; Hoenen, Thomas; Arsenault, Ryan; Feldmann, Friederike; Traynor, Dawn; Postnikova, Elena; Kusalik, Anthony; Napper, Scott; Blaney, Joseph E; Feldmann, Heinz; Jahrling, Peter B

    2014-09-01

    Ebola virus (EBOV) causes a severe hemorrhagic disease in humans and nonhuman primates, with a median case fatality rate of 78.4%. Although EBOV is considered a public health concern, there is a relative paucity of information regarding the modulation of the functional host response during infection. We employed temporal kinome analysis to investigate the relative early, intermediate, and late host kinome responses to EBOV infection in human hepatocytes. Pathway overrepresentation analysis and functional network analysis of kinome data revealed that transforming growth factor (TGF-β)-mediated signaling responses were temporally modulated in response to EBOV infection. Upregulation of TGF-β signaling in the kinome data sets correlated with the upregulation of TGF-β secretion from EBOV-infected cells. Kinase inhibitors targeting TGF-β signaling, or additional cell receptors and downstream signaling pathway intermediates identified from our kinome analysis, also inhibited EBOV replication. Further, the inhibition of select cell signaling intermediates identified from our kinome analysis provided partial protection in a lethal model of EBOV infection. To gain perspective on the cellular consequence of TGF-β signaling modulation during EBOV infection, we assessed cellular markers associated with upregulation of TGF-β signaling. We observed upregulation of matrix metalloproteinase 9, N-cadherin, and fibronectin expression with concomitant reductions in the expression of E-cadherin and claudin-1, responses that are standard characteristics of an epithelium-to-mesenchyme-like transition. Additionally, we identified phosphorylation events downstream of TGF-β that may contribute to this process. From these observations, we propose a model for a broader role of TGF-β-mediated signaling responses in the pathogenesis of Ebola virus disease. Ebola virus (EBOV), formerly Zaire ebolavirus, causes a severe hemorrhagic disease in humans and nonhuman primates and is the most

  19. The protist, Monosiga brevicollis, has a tyrosine kinase signaling network more elaborate and diverse than found in any known metazoan.

    Science.gov (United States)

    Manning, Gerard; Young, Susan L; Miller, W Todd; Zhai, Yufeng

    2008-07-15

    Tyrosine kinase signaling has long been considered a hallmark of intercellular communication, unique to multicellular animals. Our genomic analysis of the unicellular choanoflagellate Monosiga brevicollis discovers a remarkable count of 128 tyrosine kinases, 38 tyrosine phosphatases, and 123 phosphotyrosine (pTyr)-binding SH2 proteins, all higher counts than seen in any metazoan. This elaborate signaling network shows little orthology to metazoan counterparts yet displays many innovations reminiscent of metazoans. These include extracellular domains structurally related to those of metazoan receptor kinases, alternative methods for membrane anchoring and phosphotyrosine interaction in cytoplasmic kinases, and domain combinations that link kinases to small GTPase signaling and transcription. These proteins also display a wealth of combinations of known signaling domains. This uniquely divergent and elaborate signaling network illuminates the early evolution of pTyr signaling, explores innovative ways to traverse the cellular signaling circuitry, and shows extensive convergent evolution, highlighting pervasive constraints on pTyr signaling.

  20. Differential Cellular Responses to Hedgehog Signalling in Vertebrates—What is the Role of Competence?

    OpenAIRE

    Clemens Kiecker; Anthony Graham; Malcolm Logan

    2016-01-01

    A surprisingly small number of signalling pathways generate a plethora of cellular responses ranging from the acquisition of multiple cell fates to proliferation, differentiation, morphogenesis and cell death. These diverse responses may be due to the dose-dependent activities of signalling factors, or to intrinsic differences in the response of cells to a given signal—a phenomenon called differential cellular competence. In this review, we focus on temporal and spatial differences in compete...

  1. Radio resource management for mobile traffic offloading in heterogeneous cellular networks

    CERN Document Server

    Wu, Yuan; Huang, Jianwei; Shen, Xuemin (Sherman)

    2017-01-01

    This SpringerBrief offers two concrete design examples for traffic offloading. The first is an optimal resource allocation for small-cell based traffic offloading that aims at minimizing mobile users’ data cost. The second is an optimal resource allocation for device-to-device assisted traffic offloading that also minimizes the total energy consumption and cellular link usage (while providing an overview of the challenging issues). Both examples illustrate the importance of proper resource allocation to the success of traffic offloading, show the consequent performance advantages of executing optimal resource allocation, and present the methodologies to achieve the corresponding optimal offloading solution for traffic offloading in heterogeneous cellular networks. The authors also include an overview of heterogeneous cellular networks and explain different traffic offloading paradigms ranging from uplink traffic offloading through small cells to downlink traffic offloading via mobile device-to-device cooper...

  2. Neural networks in signal processing

    International Nuclear Information System (INIS)

    Govil, R.

    2000-01-01

    Nuclear Engineering has matured during the last decade. In research and design, control, supervision, maintenance and production, mathematical models and theories are used extensively. In all such applications signal processing is embedded in the process. Artificial Neural Networks (ANN), because of their nonlinear, adaptive nature are well suited to such applications where the classical assumptions of linearity and second order Gaussian noise statistics cannot be made. ANN's can be treated as nonparametric techniques, which can model an underlying process from example data. They can also adopt their model parameters to statistical change with time. Algorithms in the framework of Neural Networks in Signal processing have found new applications potentials in the field of Nuclear Engineering. This paper reviews the fundamentals of Neural Networks in signal processing and their applications in tasks such as recognition/identification and control. The topics covered include dynamic modeling, model based ANN's, statistical learning, eigen structure based processing and generalization structures. (orig.)

  3. 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.

  4. Signaling in large-scale neural networks

    DEFF Research Database (Denmark)

    Berg, Rune W; Hounsgaard, Jørn

    2009-01-01

    We examine the recent finding that neurons in spinal motor circuits enter a high conductance state during functional network activity. The underlying concomitant increase in random inhibitory and excitatory synaptic activity leads to stochastic signal processing. The possible advantages of this m......We examine the recent finding that neurons in spinal motor circuits enter a high conductance state during functional network activity. The underlying concomitant increase in random inhibitory and excitatory synaptic activity leads to stochastic signal processing. The possible advantages...... of this metabolically costly organization are analyzed by comparing with synaptically less intense networks driven by the intrinsic response properties of the network neurons....

  5. Next-Generation Environment-Aware Cellular Networks: Modern Green Techniques and Implementation Challenges

    KAUST Repository

    Ghazzai, Hakim

    2016-09-16

    Over the last decade, mobile communications have been witnessing a noteworthy increase of data traffic demand that is causing an enormous energy consumption in cellular networks. The reduction of their fossil fuel consumption in addition to the huge energy bills paid by mobile operators is considered as the most important challenges for the next-generation cellular networks. Although most of the proposed studies were focusing on individual physical layer power optimizations, there is a growing necessity to meet the green objective of fifth-generation cellular networks while respecting the user\\'s quality of service. This paper investigates four important techniques that could be exploited separately or together in order to enable wireless operators achieve significant economic benefits and environmental savings: 1) the base station sleeping strategy; 2) the optimized energy procurement from the smart grid; 3) the base station energy sharing; and 4) the green networking collaboration between competitive mobile operators. The presented simulation results measure the gain that could be obtained using these techniques compared with that of traditional scenarios. Finally, this paper discusses the issues and challenges related to the implementations of these techniques in real environments. © 2016 IEEE.

  6. Neural networks and cellular automata in experimental high energy physics

    Energy Technology Data Exchange (ETDEWEB)

    Denby, B

    1988-06-01

    Within the past few years, two novel computing techniques, cellular automata and neural networks, have shown considerable promise in the solution of problems of a very high degree of complexity, such as turbulent fluid flow, image processing, and pattern recognition. Many of the problems faced in experimental high energy physics are also of this nature. Track reconstruction in wire chambers and cluster finding in cellular calorimeters, for instance, involve pattern recognition and high combinatorial complexity since many combinations of hits or cells must be considered in order to arrive at the final tracks or clusters. Here we examine in what way connective network methods can be applied to some of the problems of experimental high energy physics. It is found that such problems as track and cluster finding adapt naturally to these approaches. When large scale hard-wired connective networks become available, it will be possible to realize solutions to such problems in a fraction of the time required by traditional methods. For certain types of problems, faster solutions are already possible using model networks implemented on vector or other massively parallel machines. It should also be possible, using existing technology, to build simplified networks that will allow detailed reconstructed event information to be used in fast trigger decisions.

  7. Neural networks and cellular automata in experimental high energy physics

    International Nuclear Information System (INIS)

    Denby, B.

    1987-11-01

    Within the past few years, two novel computing techniques, cellular automata and neural networks, have shown considerable promise in the solution of problems of a very high degree of complexity, such as turbulent fluid flow, image processing, and pattern recognition. Many of the problems faced in experimental high energy physics are also of this nature. Track reconstruction in wire chambers and cluster finding in cellular calorimeters, for instance, involve pattern recognition and high combinatorial complexity since many combinations of hits or cells must be considered in order to arrive at the final tracks or clusters. Here we examine in what way connective network methods can be applied to some of the problems of experimental high physics. It is found that such problems as track and cluster finding adapt naturally to these approaches. When large scale hardwired connective networks become available, it will be possible to realize solutions to such problems in a fraction of the time required by traditional methods. For certain types of problems, faster solutions are already possible using model networks implemented on vector or other massively parallel machines. It should also be possible, using existing technology, to build simplified networks that will allow detailed reconstructed event information to be used in fast trigger decisions

  8. Neural networks and cellular automata in experimental high energy physics

    International Nuclear Information System (INIS)

    Denby, B.

    1988-01-01

    Within the past few years, two novel computing techniques, cellular automata and neural networks, have shown considerable promise in the solution of problems of a very high degree of complexity, such as turbulent fluid flow, image processing, and pattern recognition. Many of the problems faced in experimental high energy physics are also of this nature. Track reconstruction in wire chambers and cluster finding in cellular calorimeters, for instance, involve pattern recognition and high combinatorial complexity since many combinations of hits or cells must be considered in order to arrive at the final tracks or clusters. Here we examine in what way connective network methods can be applied to some of the problems of experimental high energy physics. It is found that such problems as track and cluster finding adapt naturally to these approaches. When large scale hard-wired connective networks become available, it will be possible to realize solutions to such problems in a fraction of the time required by traditional methods. For certain types of problems, faster solutions are already possible using model networks implemented on vector or other massively parallel machines. It should also be possible, using existing technology, to build simplified networks that will allow detailed reconstructed event information to be used in fast trigger decisions. (orig.)

  9. Limits on the Capacity of In-Band Full Duplex Communication in Uplink Cellular Networks

    KAUST Repository

    Randrianantenaina, Itsikiantsoa

    2016-02-26

    Simultaneous co-channel transmission and reception, denoted as in-band full duplex (FD) communication, has been promoted as an attractive solution to improve the spectral efficiency of cellular networks. However, in addition to the selfinterference problem, cross-mode interference (i.e., between uplink and downlink) imposes a major obstacle for the deployment of FD communication in cellular networks. More specifically, the downlink to uplink interference represents the performance bottleneck for FD operation due to the uplink limited transmission power and venerable operation when compared to the downlink counterpart. While the positive impact of FD communication to the downlink performance has been proved in the literature, its effect on the uplink transmission has been neglected. This paper focuses on the effect of downlink interference on the uplink transmission in FD cellular networks in order to see whether FD communication is beneficial for the uplink transmission or not, and if yes for which type of network. To quantify the expected performance gains, we derive a closed form expression of the maximum achievable uplink capacity in FD cellular networks. In contrast to the downlink capacity which always improves with FD communication, our results show that the uplink performance may improves or degrades depending on the associated network parameters. Particularly, we show that the intensity of base stations (BSs) has a more prominent effect on the uplink performance than their transmission power.

  10. Limits on the Capacity of In-Band Full Duplex Communication in Uplink Cellular Networks

    KAUST Repository

    Randrianantenaina, Itsikiantsoa; Elsawy, Hesham; Alouini, Mohamed-Slim

    2016-01-01

    Simultaneous co-channel transmission and reception, denoted as in-band full duplex (FD) communication, has been promoted as an attractive solution to improve the spectral efficiency of cellular networks. However, in addition to the selfinterference problem, cross-mode interference (i.e., between uplink and downlink) imposes a major obstacle for the deployment of FD communication in cellular networks. More specifically, the downlink to uplink interference represents the performance bottleneck for FD operation due to the uplink limited transmission power and venerable operation when compared to the downlink counterpart. While the positive impact of FD communication to the downlink performance has been proved in the literature, its effect on the uplink transmission has been neglected. This paper focuses on the effect of downlink interference on the uplink transmission in FD cellular networks in order to see whether FD communication is beneficial for the uplink transmission or not, and if yes for which type of network. To quantify the expected performance gains, we derive a closed form expression of the maximum achievable uplink capacity in FD cellular networks. In contrast to the downlink capacity which always improves with FD communication, our results show that the uplink performance may improves or degrades depending on the associated network parameters. Particularly, we show that the intensity of base stations (BSs) has a more prominent effect on the uplink performance than their transmission power.

  11. Using Regularization to Infer Cell Line Specificity in Logical Network Models of Signaling Pathways

    Directory of Open Access Journals (Sweden)

    Sébastien De Landtsheer

    2018-05-01

    Full Text Available Understanding the functional properties of cells of different origins is a long-standing challenge of personalized medicine. Especially in cancer, the high heterogeneity observed in patients slows down the development of effective cures. The molecular differences between cell types or between healthy and diseased cellular states are usually determined by the wiring of regulatory networks. Understanding these molecular and cellular differences at the systems level would improve patient stratification and facilitate the design of rational intervention strategies. Models of cellular regulatory networks frequently make weak assumptions about the distribution of model parameters across cell types or patients. These assumptions are usually expressed in the form of regularization of the objective function of the optimization problem. We propose a new method of regularization for network models of signaling pathways based on the local density of the inferred parameter values within the parameter space. Our method reduces the complexity of models by creating groups of cell line-specific parameters which can then be optimized together. We demonstrate the use of our method by recovering the correct topology and inferring accurate values of the parameters of a small synthetic model. To show the value of our method in a realistic setting, we re-analyze a recently published phosphoproteomic dataset from a panel of 14 colon cancer cell lines. We conclude that our method efficiently reduces model complexity and helps recovering context-specific regulatory information.

  12. Collaborative Multi-Layer Network Coding For Hybrid Cellular Cognitive Radio Networks

    KAUST Repository

    Moubayed, Abdallah J.

    2014-05-01

    In this thesis, as an extension to [1], we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in hybrid (interweave and underlay) cellular cognitive radio networks. This scheme allows the uncoordinated collaboration between the collocated primary and cognitive radio base-stations in order to minimize their own as well as each other’s packet recovery overheads, thus by improving their throughput. The proposed scheme ensures that each network’s performance is not degraded by its help to the other network. Moreover, it guarantees that the primary network’s interference threshold is not violated in the same and adjacent cells. Yet, the scheme allows the reduction of the recovery overhead in the collocated primary and cognitive radio networks. The reduction in the cognitive radio network is further amplified due to the perfect detection of spectrum holes which allows the cognitive radio base station to transmit at higher power without fear of violating the interference threshold of the primary network. For the secondary network, simulation results show reductions of 20% and 34% in the packet recovery overhead, compared to the non-collaborative scheme, for low and high probabilities of primary packet arrivals, respectively. For the primary network, this reduction was found to be 12%. Furthermore, with the use of fractional cooperation, the average recovery overhead is further reduced by around 5% for the primary network and around 10% for the secondary network when a high fractional cooperation probability is used.

  13. Computational study of noise in a large signal transduction network

    Directory of Open Access Journals (Sweden)

    Ruohonen Keijo

    2011-06-01

    Full Text Available Abstract Background Biochemical systems are inherently noisy due to the discrete reaction events that occur in a random manner. Although noise is often perceived as a disturbing factor, the system might actually benefit from it. In order to understand the role of noise better, its quality must be studied in a quantitative manner. Computational analysis and modeling play an essential role in this demanding endeavor. Results We implemented a large nonlinear signal transduction network combining protein kinase C, mitogen-activated protein kinase, phospholipase A2, and β isoform of phospholipase C networks. We simulated the network in 300 different cellular volumes using the exact Gillespie stochastic simulation algorithm and analyzed the results in both the time and frequency domain. In order to perform simulations in a reasonable time, we used modern parallel computing techniques. The analysis revealed that time and frequency domain characteristics depend on the system volume. The simulation results also indicated that there are several kinds of noise processes in the network, all of them representing different kinds of low-frequency fluctuations. In the simulations, the power of noise decreased on all frequencies when the system volume was increased. Conclusions We concluded that basic frequency domain techniques can be applied to the analysis of simulation results produced by the Gillespie stochastic simulation algorithm. This approach is suited not only to the study of fluctuations but also to the study of pure noise processes. Noise seems to have an important role in biochemical systems and its properties can be numerically studied by simulating the reacting system in different cellular volumes. Parallel computing techniques make it possible to run massive simulations in hundreds of volumes and, as a result, accurate statistics can be obtained from computational studies.

  14. Area Green Efficiency (AGE) of Two Tier Heterogeneous Cellular Networks

    KAUST Repository

    Tabassum, Hina

    2012-10-03

    Small cell networks are becoming standard part of the future heterogeneous networks. In this paper, we consider a two tier heterogeneous network which promises energy savings by integrating the femto and macro cellular networks and thereby reducing CO2 emissions, operational and capital expenditures (OPEX and CAPEX) whilst enhancing the area spectral efficiency (ASE) of the network. In this context, we define a performance metric which characterize the aggregate energy savings per unit macrocell area and is referred to as area green efficiency (AGE) of the two tier heterogeneous network where the femto base stations are arranged around the edge of the reference macrocell such that the configuration is referred to as femto-on-edge (FOE). The mobile users in macro and femto cellular networks are transmitting with the adaptive power while maintaining the desired link quality such that the energy aware FOE configuration mandates to (i) save energy, and (ii) reduce the co-channel interference. We present a mathematical analysis to incorporate the uplink power control mechanism adopted by the mobile users and calibrate the uplink ASE and AGE of the energy aware FOE configuration. Next, we derive analytical expressions to compute the bounds on the uplink ASE of energy aware FOE configuration and demonstrate that the derived bounds are useful in evaluating the ASE under worst and best case interference scenarios. Simulation results are produced to demonstrate the ASE and AGE improvements in comparison to macro-only and macro-femto configuration with uniformly distributed femtocells.

  15. Nitric Oxide Synthase and Cyclooxygenase Pathways: A Complex Interplay in Cellular Signaling.

    Science.gov (United States)

    Sorokin, Andrey

    2016-01-01

    The cellular reaction to external challenges is a tightly regulated process consisting of integrated processes mediated by a variety of signaling molecules, generated as a result of modulation of corresponding biosynthetic systems. Both, nitric oxide synthase (NOS) and cyclooxygenase (COX) systems, consist of constitutive forms (NOS1, NOS3 and COX-1), which are mostly involved in housekeeping tasks, and inducible forms (NOS2 and COX-2), which shape the cellular response to stress and variety of bioactive agents. The complex interplay between NOS and COX pathways can be observed at least at three levels. Firstly, products of NOS and Cox systems can mediate the regulation and the expression of inducible forms (NOS2 and COX-2) in response of similar and dissimilar stimulus. Secondly, the reciprocal modulation of cyclooxygenase activity by nitric oxide and NOS activity by prostaglandins at the posttranslational level has been shown to occur. Mechanisms by which nitric oxide can modulate prostaglandin synthesis include direct S-nitrosylation of COX and inactivation of prostaglandin I synthase by peroxynitrite, product of superoxide reaction with nitric oxide. Prostaglandins, conversely, can promote an increased association of dynein light chain (DLC) (also known as protein inhibitor of neuronal nitric oxide synthase) with NOS1, thereby reducing its activity. The third level of interplay is provided by intracellular crosstalk of signaling pathways stimulated by products of NOS and COX which contributes significantly to the complexity of cellular signaling. Since modulation of COX and NOS pathways was shown to be principally involved in a variety of pathological conditions, the dissection of their complex relationship is needed for better understanding of possible therapeutic strategies. This review focuses on implications of interplay between NOS and COX for cellular function and signal integration.

  16. Distributed Velocity-Dependent Protocol for Multihop Cellular Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jagyasi Bhushan

    2009-01-01

    Full Text Available Abstract Cell phones are embedded with sensors form a Cellular Sensor Network which can be used to localize a moving event. The inherent mobility of the application and of the cell phone users warrants distributed structure-free data aggregation and on-the-fly routing. We propose a Distributed Velocity-Dependent (DVD protocol to localize a moving event using a Multihop Cellular Sensor Network (MCSN. DVD is based on a novel form of connectivity determined by the waiting time of nodes for a Random Waypoint (RWP distribution of cell phone users. This paper analyzes the time-stationary and spatial distribution of the proposed waiting time to explain the superior event localization and delay performances of DVD over the existing Randomized Waiting (RW protocol. A sensitivity analysis is also performed to compare the performance of DVD with RW and the existing Centralized approach.

  17. Evolution of Positioning Techniques in Cellular Networks, from 2G to 4G

    Directory of Open Access Journals (Sweden)

    Rafael Saraiva Campos

    2017-01-01

    Full Text Available This review paper presents within a common framework the mobile station positioning methods applied in 2G, 3G, and 4G cellular networks, as well as the structure of the related 3GPP technical specifications. The evolution path through the generations is explored in three steps at each level: first, the new network elements supporting localization features are introduced; then, the standard localization methods are described; finally, the protocols providing specific support to mobile station positioning are studied. To allow a better understanding, this paper also brings a brief review of the cellular networks evolution paths.

  18. Enhancement of Localization Accuracy in Cellular Networks via Cooperative AdHoc Links

    DEFF Research Database (Denmark)

    Lhomme, Edouard; Frattasi, Simone; Figueiras, Joao

    2006-01-01

    Positioning information enables new applications for cellular phones, personal communication systems, and specialized mobile radios. The network heterogeneity emerging in the fourth generation (4G) of mobile networks can be utilized for enhancements of the location estimation accuracy...

  19. Green collaboration in cognitive radio cellular networks with roaming and spectrum trading

    KAUST Repository

    Sboui, Lokman; Ghazzai, Hakim; Rezki, Zouheir; Alouini, Mohamed-Slim

    2015-01-01

    In this paper, we propose a new cognitive cellular network architecture based on the coexistence of primary and secondary networks, (PN) and (SN), respectively. The PN aims to minimize its energy consumption by switching off the maximum number

  20. Reconstruction of periodic signals using neural networks

    Directory of Open Access Journals (Sweden)

    José Danilo Rairán Antolines

    2014-01-01

    Full Text Available In this paper, we reconstruct a periodic signal by using two neural networks. The first network is trained to approximate the period of a signal, and the second network estimates the corresponding coefficients of the signal's Fourier expansion. The reconstruction strategy consists in minimizing the mean-square error via backpro-pagation algorithms over a single neuron with a sine transfer function. Additionally, this paper presents mathematical proof about the quality of the approximation as well as a first modification of the algorithm, which requires less data to reach the same estimation; thus making the algorithm suitable for real-time implementations.

  1. The Genome-Scale Integrated Networks in Microorganisms

    Directory of Open Access Journals (Sweden)

    Tong Hao

    2018-02-01

    Full Text Available The genome-scale cellular network has become a necessary tool in the systematic analysis of microbes. In a cell, there are several layers (i.e., types of the molecular networks, for example, genome-scale metabolic network (GMN, transcriptional regulatory network (TRN, and signal transduction network (STN. It has been realized that the limitation and inaccuracy of the prediction exist just using only a single-layer network. Therefore, the integrated network constructed based on the networks of the three types attracts more interests. The function of a biological process in living cells is usually performed by the interaction of biological components. Therefore, it is necessary to integrate and analyze all the related components at the systems level for the comprehensively and correctly realizing the physiological function in living organisms. In this review, we discussed three representative genome-scale cellular networks: GMN, TRN, and STN, representing different levels (i.e., metabolism, gene regulation, and cellular signaling of a cell’s activities. Furthermore, we discussed the integration of the networks of the three types. With more understanding on the complexity of microbial cells, the development of integrated network has become an inevitable trend in analyzing genome-scale cellular networks of microorganisms.

  2. PV-Powered CoMP-Based Green Cellular Networks with a Standby Grid Supply

    Directory of Open Access Journals (Sweden)

    Abu Jahid

    2017-01-01

    Full Text Available This paper proposes a novel framework for PV-powered cellular networks with a standby grid supply and an essential energy management technique for achieving envisaged green networks. The proposal considers an emerging cellular network architecture employing two types of coordinated multipoint (CoMP transmission techniques for serving the subscribers. Under the proposed framework, each base station (BS is powered by an individual PV solar energy module having an independent storage device. BSs are also connected to the conventional grid supply for meeting additional energy demand. We also propose a dynamic inter-BS solar energy sharing policy through a transmission line for further greening the proposed network by minimizing the consumption from the grid supply. An extensive simulation-based study in the downlink of a Long-Term Evolution (LTE cellular system is carried out for evaluating the energy efficiency performance of the proposed framework. System performance is also investigated for identifying the impact of various system parameters including storage factor, storage capacity, solar generation capacity, transmission line loss, and different CoMP techniques.

  3. Taming the sphinx: Mechanisms of cellular sphingolipid homeostasis.

    Science.gov (United States)

    Olson, D K; Fröhlich, F; Farese, R V; Walther, T C

    2016-08-01

    Sphingolipids are important structural membrane components of eukaryotic cells, and potent signaling molecules. As such, their levels must be maintained to optimize cellular functions in different cellular membranes. Here, we review the current knowledge of homeostatic sphingolipid regulation. We describe recent studies in Saccharomyces cerevisiae that have provided insights into how cells sense changes in sphingolipid levels in the plasma membrane and acutely regulate sphingolipid biosynthesis by altering signaling pathways. We also discuss how cellular trafficking has emerged as an important determinant of sphingolipid homeostasis. Finally, we highlight areas where work is still needed to elucidate the mechanisms of sphingolipid regulation and the physiological functions of such regulatory networks, especially in mammalian cells. This article is part of a Special Issue entitled: The cellular lipid landscape edited by Tim P. Levine and Anant K. Menon. Copyright © 2015. Published by Elsevier B.V.

  4. A fuzzy neural network for sensor signal estimation

    International Nuclear Information System (INIS)

    Na, Man Gyun

    2000-01-01

    In this work, a fuzzy neural network is used to estimate the relevant sensor signal using other sensor signals. Noise components in input signals into the fuzzy neural network are removed through the wavelet denoising technique. Principal component analysis (PCA) is used to reduce the dimension of an input space without losing a significant amount of information. A lower dimensional input space will also usually reduce the time necessary to train a fuzzy-neural network. Also, the principal component analysis makes easy the selection of the input signals into the fuzzy neural network. The fuzzy neural network parameters are optimized by two learning methods. A genetic algorithm is used to optimize the antecedent parameters of the fuzzy neural network and a least-squares algorithm is used to solve the consequent parameters. The proposed algorithm was verified through the application to the pressurizer water level and the hot-leg flowrate measurements in pressurized water reactors

  5. Differential roles of AVP and VIP signaling in the postnatal changes of neural networks for coherent circadian rhythms in the SCN

    Science.gov (United States)

    Ono, Daisuke; Honma, Sato; Honma, Ken-ichi

    2016-01-01

    The suprachiasmatic nucleus (SCN) is the site of the master circadian clock in mammals. The SCN neural network plays a critical role in expressing the tissue-level circadian rhythm. Previously, we demonstrated postnatal changes in the SCN network in mice, in which the clock gene products CRYPTOCHROMES (CRYs) are involved. Here, we show that vasoactive intestinal polypeptide (VIP) signaling is essential for the tissue-level circadian PER2::LUC rhythm in the neonatal SCN of CRY double-deficient mice (Cry1,2−/−). VIP and arginine vasopressin (AVP) signaling showed redundancy in expressing the tissue-level circadian rhythm in the SCN. AVP synthesis was significantly attenuated in the Cry1,2−/− SCN, which contributes to aperiodicity in the adult mice together with an attenuation of VIP signaling as a natural process of ontogeny. The SCN network consists of multiple clusters of cellular circadian rhythms that are differentially integrated by AVP and VIP signaling, depending on the postnatal period. PMID:27626074

  6. Detection of silent cells, synchronization and modulatory activity in developing cellular networks.

    NARCIS (Netherlands)

    Hjorth, J.J.J.; Dawitz, J.; Kroon, T.; da Silva Dias Pires, J.H.; Dassen, V.J.; Berkhout, J.A.; Emperador Melero, J.; Nadadhur, A.G.; Alevra, M.; Toonen, R.F.G.; Heine, V.M.; Mansvelder, H.D.; Meredith, R.M.

    2016-01-01

    Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell

  7. Silymarin Suppresses Cellular Inflammation By Inducing Reparative Stress Signaling

    Energy Technology Data Exchange (ETDEWEB)

    Lovelace, Erica S.; Wagoner, Jessica; MacDonald, James; Bammler, Theo; Bruckner, Jacob; Brownell, Jessica; Beyer, Richard; Zink, Erika M.; Kim, Young-Mo; Kyle, Jennifer E.; Webb-Robertson, Bobbie-Jo M.; Waters, Katrina M.; Metz, Thomas O.; Farin, Federico; Oberlies, Nicholas H.; Polyak, Steve

    2015-08-28

    Silymarin (SM), a natural product, is touted as a liver protectant and preventer of both chronic inflammation and diseases. To define how SM elicits these effects at a systems level, we performed transcriptional profiling, metabolomics, and signaling studies in human liver and T cell lines. Multiple pathways associated with cellular stress and metabolism were modulated by SM treatment within 0.5 to four hours: activation of Activating Transcription Factor 4 (ATF-4) and adenosine monophosphate protein kinase (AMPK) and inhibition of mammalian target of rapamycin (mTOR) signaling, the latter being associated with induction of DNA-damage-inducible transcript 4 (DDIT4). Metabolomics analyses revealed suppression of glycolytic, TCA cycle, and amino acid metabolism by SM treatment. Antiinflammatory effects arose with prolonged (i.e. 24 hours) SM exposure, with suppression of multiple proinflammatory mRNAs and nuclear factor kappa B (NF-κB) and forkhead box O (FOXO) signaling. Studies with murine knock out cells revealed that SM inhibition of both mTOR and NF-κB was partially AMPK dependent, while SM inhibition of the mTOR pathway in part required DDIT4. Thus, SM activates stress and repair responses that culminate in an anti-inflammatory phenotype. Other natural products induced similar stress responses, which correlated with their ability to suppress inflammation. Therefore, natural products like SM may be useful as tools to define how metabolic, stress, and repair pathways regulate cellular inflammation.

  8. Processing of seismic signals from a seismometer network

    International Nuclear Information System (INIS)

    Key, F.A.; Warburton, P.J.

    1983-08-01

    A description is given of the Seismometer Network Analysis Computer (SNAC) which processes short period data from a network of seismometers (UKNET). The nine stations of the network are distributed throughout the UK and their outputs are transmitted to a control laboratory (Blacknest) where SNAC monitors the data for seismic signals. The computer gives an estimate of the source location of the detected signals and stores the waveforms. The detection logic is designed to maintain high sensitivity without excessive ''false alarms''. It is demonstrated that the system is able to detect seismic signals at an amplitude level consistent with a network of single stations and, within the limitations of signal onset time measurements made by machine, can locate the source of the seismic disturbance. (author)

  9. On the holistic approach in cellular and cancer biology: nonlinearity, complexity, and quasi-determinism of the dynamic cellular network.

    Science.gov (United States)

    Waliszewski, P; Molski, M; Konarski, J

    1998-06-01

    A keystone of the molecular reductionist approach to cellular biology is a specific deductive strategy relating genotype to phenotype-two distinct categories. This relationship is based on the assumption that the intermediary cellular network of actively transcribed genes and their regulatory elements is deterministic (i.e., a link between expression of a gene and a phenotypic trait can always be identified, and evolution of the network in time is predetermined). However, experimental data suggest that the relationship between genotype and phenotype is nonbijective (i.e., a gene can contribute to the emergence of more than just one phenotypic trait or a phenotypic trait can be determined by expression of several genes). This implies nonlinearity (i.e., lack of the proportional relationship between input and the outcome), complexity (i.e. emergence of the hierarchical network of multiple cross-interacting elements that is sensitive to initial conditions, possesses multiple equilibria, organizes spontaneously into different morphological patterns, and is controlled in dispersed rather than centralized manner), and quasi-determinism (i.e., coexistence of deterministic and nondeterministic events) of the network. Nonlinearity within the space of the cellular molecular events underlies the existence of a fractal structure within a number of metabolic processes, and patterns of tissue growth, which is measured experimentally as a fractal dimension. Because of its complexity, the same phenotype can be associated with a number of alternative sequences of cellular events. Moreover, the primary cause initiating phenotypic evolution of cells such as malignant transformation can be favored probabilistically, but not identified unequivocally. Thermodynamic fluctuations of energy rather than gene mutations, the material traits of the fluctuations alter both the molecular and informational structure of the network. Then, the interplay between deterministic chaos, complexity, self

  10. Differential Cellular Responses to Hedgehog Signalling in Vertebrates—What is the Role of Competence?

    Science.gov (United States)

    Kiecker, Clemens; Graham, Anthony; Logan, Malcolm

    2016-01-01

    A surprisingly small number of signalling pathways generate a plethora of cellular responses ranging from the acquisition of multiple cell fates to proliferation, differentiation, morphogenesis and cell death. These diverse responses may be due to the dose-dependent activities of signalling factors, or to intrinsic differences in the response of cells to a given signal—a phenomenon called differential cellular competence. In this review, we focus on temporal and spatial differences in competence for Hedgehog (HH) signalling, a signalling pathway that is reiteratively employed in embryos and adult organisms. We discuss the upstream signals and mechanisms that may establish differential competence for HHs in a range of different tissues. We argue that the changing competence for HH signalling provides a four-dimensional framework for the interpretation of the signal that is essential for the emergence of functional anatomy. A number of diseases—including several types of cancer—are caused by malfunctions of the HH pathway. A better understanding of what provides differential competence for this signal may reveal HH-related disease mechanisms and equip us with more specific tools to manipulate HH signalling in the clinic. PMID:29615599

  11. Differential Cellular Responses to Hedgehog Signalling in Vertebrates—What is the Role of Competence?

    Directory of Open Access Journals (Sweden)

    Clemens Kiecker

    2016-12-01

    Full Text Available A surprisingly small number of signalling pathways generate a plethora of cellular responses ranging from the acquisition of multiple cell fates to proliferation, differentiation, morphogenesis and cell death. These diverse responses may be due to the dose-dependent activities of signalling factors, or to intrinsic differences in the response of cells to a given signal—a phenomenon called differential cellular competence. In this review, we focus on temporal and spatial differences in competence for Hedgehog (HH signalling, a signalling pathway that is reiteratively employed in embryos and adult organisms. We discuss the upstream signals and mechanisms that may establish differential competence for HHs in a range of different tissues. We argue that the changing competence for HH signalling provides a four-dimensional framework for the interpretation of the signal that is essential for the emergence of functional anatomy. A number of diseases—including several types of cancer—are caused by malfunctions of the HH pathway. A better understanding of what provides differential competence for this signal may reveal HH-related disease mechanisms and equip us with more specific tools to manipulate HH signalling in the clinic.

  12. The EH network

    DEFF Research Database (Denmark)

    Santolini, E; Salcini, A E; Kay, B K

    1999-01-01

    . Moreover, a number of cellular ligands of the domain have been identified and demonstrated to define a complex network of protein-protein interactions in the eukaryotic cell. Interestingly, many of the EH-containing and EH-binding proteins display characteristics of endocytic "accessory" proteins......, suggesting that the principal function of the EH network is to regulate various steps in endocytosis. In addition, recent evidence suggests that the EH network might work as an "integrator" of signals controlling cellular pathways as diverse as endocytosis, nucleocytosolic export, and ultimately cell...

  13. Using Cellular Automata to Investigate Pedestrian Conflicts with Vehicles in Crosswalk at Signalized Intersection

    Directory of Open Access Journals (Sweden)

    Xiaomeng Li

    2012-01-01

    Full Text Available The operational efficiency and safety of pedestrian flows at intersections is an important aspect of urban traffic. Particularly, conflicts between pedestrians and vehicles in crosswalk are one of the most influential factors for intersection safety. This paper presents a cellular automata model that simulates pedestrian and vehicle crossing behaviors at signalized intersections. Through the simulation, we investigate the effects of different pedestrian signal timing and crosswalk widths on the crosswalk capacity, the number of traffic conflicts between pedestrians and vehicles, and pedestrian delay due to the conflicts. The simulation results indicate that the cellular automata is an effective simulation platform for investigating complex pedestrian-related traffic phenomenon at signalized intersections.

  14. Cellular Controlled Short-Range Communication for Cooperative P2P Networking

    DEFF Research Database (Denmark)

    Fitzek, Frank H. P.; Katz, Marcos; Zhang, Qi

    2009-01-01

    -range communication network among cooperating mobile and wireless devices. The role of the mobile device will change, from being an agnostic entity in respect to the surrounding world to a cognitive device. This cognitive device is capable of being aware of the neighboring devices as well as on the possibility......This article advocates a novel communication architecture and associated collaborative framework for future wireless communication systems. In contrast to the dominating cellular architecture and the upcoming peer-to-peer architecture, the new approach envisions a cellular controlled short...... to establish cooperation with them. The novel architecture together with several possible cooperative strategies will bring clear benefits for the network and service providers, mobile device manufacturers and also end users....

  15. The function of endocytosis in Wnt signaling.

    Science.gov (United States)

    Brunt, Lucy; Scholpp, Steffen

    2018-03-01

    Wnt growth factors regulate one of the most important signaling networks during development, tissue homeostasis and disease. Despite the biological importance of Wnt signaling, the mechanism of endocytosis during this process is ill described. Wnt molecules can act as paracrine signals, which are secreted from the producing cells and transported through neighboring tissue to activate signaling in target cells. Endocytosis of the ligand is important at several stages of action: One central function of endocytic trafficking in the Wnt pathway occurs in the source cell. Furthermore, the β-catenin-dependent Wnt ligands require endocytosis for signal activation and to regulate gene transcription in the responding cells. Alternatively, Wnt/β-catenin-independent signaling regulates endocytosis of cell adherence plaques to control cell migration. In this comparative review, we elucidate these three fundamental interconnected functions, which together regulate cellular fate and cellular behavior. Based on established hypotheses and recent findings, we develop a revised picture for the complex function of endocytosis in the Wnt signaling network.

  16. Controlling Depth of Cellular Quiescence by an Rb-E2F Network Switch

    Directory of Open Access Journals (Sweden)

    Jungeun Sarah Kwon

    2017-09-01

    Full Text Available Quiescence is a non-proliferative cellular state that is critical to tissue repair and regeneration. Although often described as the G0 phase, quiescence is not a single homogeneous state. As cells remain quiescent for longer durations, they move progressively deeper and display a reduced sensitivity to growth signals. Deep quiescent cells, unlike senescent cells, can still re-enter the cell cycle under physiological conditions. Mechanisms controlling quiescence depth are poorly understood, representing a currently underappreciated layer of complexity in growth control. Here, we show that the activation threshold of a Retinoblastoma (Rb-E2F network switch controls quiescence depth. Particularly, deeper quiescent cells feature a higher E2F-switching threshold and exhibit a delayed traverse through the restriction point (R-point. We further show that different components of the Rb-E2F network can be experimentally perturbed, following computer model predictions, to coarse- or fine-tune the E2F-switching threshold and drive cells into varying quiescence depths.

  17. Exponential stability of delayed fuzzy cellular neural networks with diffusion

    International Nuclear Information System (INIS)

    Huang Tingwen

    2007-01-01

    The exponential stability of delayed fuzzy cellular neural networks (FCNN) with diffusion is investigated. Exponential stability, significant for applications of neural networks, is obtained under conditions that are easily verified by a new approach. Earlier results on the exponential stability of FCNN with time-dependent delay, a special case of the model studied in this paper, are improved without using the time-varying term condition: dτ(t)/dt < μ

  18. A performance based evaluation of SIP signalling across converged networks

    NARCIS (Netherlands)

    Oredope, A.; Liotta, A.

    2007-01-01

    As wireless networks evolves towards the 3G and 4G architectures the mobile core networks provides a platform for all-IP convergence of mobile and fixed networks allowing for better integration of the Internet and cellular networks, providing better quality of service, charging mechanisms and

  19. LTE-A cellular networks multi-hop relay for coverage, capacity and performance enhancement

    CERN Document Server

    Yahya, Abid

    2017-01-01

    In this book, three different methods are presented to enhance the capacity and coverage area in LTE-A cellular networks. The scope involves the evaluation of the effect of the RN location in terms of capacity and the determination of the optimum location of the relay that provides maximum achievable data rate for users with limited interference at the cell boundaries. This book presents a new model to enhance both capacity and coverage area in LTE-A cellular network by determining the optimum location for the RN with limited interference. The new model is designed to enhance the capacity of the relay link by employing two antennas in RN. This design enables the relay link to absorb more users at cell edge regions. An algorithm called the Balance Power Algorithm (BPA) is developed to reduce MR power consumption. The book pertains to postgraduate students and researchers in wireless & mobile communications. Provides a variety of methods for enhancing capacity and coverage in LTE-A cellular networks Develop...

  20. A learning algorithm for oscillatory cellular neural networks.

    Science.gov (United States)

    Ho, C Y.; Kurokawa, H

    1999-07-01

    We present a cellular type oscillatory neural network for temporal segregation of stationary input patterns. The model comprises an array of locally connected neural oscillators with connections limited to a 4-connected neighborhood. The architecture is reminiscent of the well-known cellular neural network that consists of local connection for feature extraction. By means of a novel learning rule and an initialization scheme, global synchronization can be accomplished without incurring any erroneous synchrony among uncorrelated objects. Each oscillator comprises two mutually coupled neurons, and neurons share a piecewise-linear activation function characteristic. The dynamics of traditional oscillatory models is simplified by using only one plastic synapse, and the overall complexity for hardware implementation is reduced. Based on the connectedness of image segments, it is shown that global synchronization and desynchronization can be achieved by means of locally connected synapses, and this opens up a tremendous application potential for the proposed architecture. Furthermore, by using special grouping synapses it is demonstrated that temporal segregation of overlapping gray-level and color segments can also be achieved. Finally, simulation results show that the learning rule proposed circumvents the problem of component mismatches, and hence facilitates a large-scale integration.

  1. On mode selection and power control for uplink D2D communication in cellular networks

    KAUST Repository

    Ali, Konpal S.

    2015-06-08

    Device-to-device (D2D) communication enables users lying in close proximity to bypass the cellular base station (BS) and transmit to one another directly. This offloads traffic from the cellular network, improves spatial frequency reuse and energy efficiency in the network. We present a comprehensive and tractable analytical framework for D2D-enabled uplink cellular networks with two different flexible mode-selection schemes. The power-control cutoff thresholds of the two communication modes have been decoupled unlike past work on the subject. We find that for a given network, an optimal value exists not only for the biased mode selection criterion, but also for r, the ratio of the power-control cutoff thresholds of the two communication modes, which maximizes spatial spectral efficiency. Also, r turns out to be a more robust parameter for optimizing network performance. Further, it is shown that the second scheme, which prioritizes spatial frequency reuse over the per-user achievable performance compared to the first scheme, achieves almost the same overall network performance; thereby trading per user performance to serve a larger number of users.

  2. On mode selection and power control for uplink D2D communication in cellular networks

    KAUST Repository

    Ali, Konpal S.; Elsawy, Hesham; Alouini, Mohamed-Slim

    2015-01-01

    Device-to-device (D2D) communication enables users lying in close proximity to bypass the cellular base station (BS) and transmit to one another directly. This offloads traffic from the cellular network, improves spatial frequency reuse and energy efficiency in the network. We present a comprehensive and tractable analytical framework for D2D-enabled uplink cellular networks with two different flexible mode-selection schemes. The power-control cutoff thresholds of the two communication modes have been decoupled unlike past work on the subject. We find that for a given network, an optimal value exists not only for the biased mode selection criterion, but also for r, the ratio of the power-control cutoff thresholds of the two communication modes, which maximizes spatial spectral efficiency. Also, r turns out to be a more robust parameter for optimizing network performance. Further, it is shown that the second scheme, which prioritizes spatial frequency reuse over the per-user achievable performance compared to the first scheme, achieves almost the same overall network performance; thereby trading per user performance to serve a larger number of users.

  3. Modeling virtualized downlink cellular networks with ultra-dense small cells

    KAUST Repository

    Ibrahim, Hazem; Elsawy, Hesham; Nguyen, Uyen T.; Alouini, Mohamed-Slim

    2015-01-01

    -to-interference-plus-noise-ratio (SINR) performance, hence, increases the spatial spectral efficiency and improves the overall network performance. However, control signaling in such dense networks consumes considerable bandwidth and limits the densification gain. Radio access network

  4. Cytokine expression and signaling in drug-induced cellular senescence

    Czech Academy of Sciences Publication Activity Database

    Nováková, Zora; Hubáčková, Soňa; Košař, Martin; Janderová-Rossmeislová, Lenka; Dobrovolná, Jana; Vašicová, Pavla; Vančurová, Markéta; Hořejší, Zuzana; Hozák, Pavel; Bartek, Jiří; Hodný, Zdeněk

    2010-01-01

    Roč. 29, č. 2 (2010), s. 273-284 ISSN 0950-9232 R&D Projects: GA AV ČR IAA500390501; GA ČR GA204/08/1418; GA MŠk LC545 Grant - others:EC(XE) TRIREME Institutional research plan: CEZ:AV0Z50520514; CEZ:AV0Z50200510 Keywords : cellular senescence * cytokines * JAK/STAT signaling pathway Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 7.414, year: 2010

  5. A NOVEL PIPELINE FOR DRUG DISCOVERY IN NEUROPSYCHIATRIC DISORDERS USING HIGH-CONTENT SINGLE-CELL SCREENING OF SIGNALLING NETWORK RESPONSES EX VIVO

    OpenAIRE

    Lago Cooke, Santiago Guillermo

    2016-01-01

    The current work entails the development of a novel high content platform for the measurement of kinetic ligand responses across cell signalling networks at the single-cell level in distinct PBMC subtypes ex vivo. Using automated sample preparation, fluorescent cellular barcoding and flow cytometry the platform is capable of detecting 21, 840 parallel cell signalling responses in each PBMC sample. We apply this platform to characterize the effects of neuropsychiatric treatments and CNS ligand...

  6. RMOD: a tool for regulatory motif detection in signaling network.

    Directory of Open Access Journals (Sweden)

    Jinki Kim

    Full Text Available Regulatory motifs are patterns of activation and inhibition that appear repeatedly in various signaling networks and that show specific regulatory properties. However, the network structures of regulatory motifs are highly diverse and complex, rendering their identification difficult. Here, we present a RMOD, a web-based system for the identification of regulatory motifs and their properties in signaling networks. RMOD finds various network structures of regulatory motifs by compressing the signaling network and detecting the compressed forms of regulatory motifs. To apply it into a large-scale signaling network, it adopts a new subgraph search algorithm using a novel data structure called path-tree, which is a tree structure composed of isomorphic graphs of query regulatory motifs. This algorithm was evaluated using various sizes of signaling networks generated from the integration of various human signaling pathways and it showed that the speed and scalability of this algorithm outperforms those of other algorithms. RMOD includes interactive analysis and auxiliary tools that make it possible to manipulate the whole processes from building signaling network and query regulatory motifs to analyzing regulatory motifs with graphical illustration and summarized descriptions. As a result, RMOD provides an integrated view of the regulatory motifs and mechanism underlying their regulatory motif activities within the signaling network. RMOD is freely accessible online at the following URL: http://pks.kaist.ac.kr/rmod.

  7. Near-Optimal Resource Allocation in Cooperative Cellular Networks Using Genetic Algorithms

    OpenAIRE

    Luo, Zihan; Armour, Simon; McGeehan, Joe

    2015-01-01

    This paper shows how a genetic algorithm can be used as a method of obtaining the near-optimal solution of the resource block scheduling problem in a cooperative cellular network. An exhaustive search is initially implementedto guarantee that the optimal result, in terms of maximizing the bandwidth efficiency of the overall network, is found, and then the genetic algorithm with the properly selected termination conditions is used in the same network. The simulation results show that the genet...

  8. Modeling cellular networks in fading environments with dominant specular components

    KAUST Repository

    Alammouri, Ahmad; Elsawy, Hesham; Salem, Ahmed Sultan; Di Renzo, Marco; Alouini, Mohamed-Slim

    2016-01-01

    to the Nakagami-m fading in some special cases. However, neither the Rayleigh nor the Nakagami-m accounts for dominant specular components (DSCs) which may appear in realistic fading channels. In this paper, we present a tractable model for cellular networks

  9. Global exponential stability of fuzzy cellular neural networks with delays and reaction-diffusion terms

    International Nuclear Information System (INIS)

    Wang Jian; Lu Junguo

    2008-01-01

    In this paper, we study the global exponential stability of fuzzy cellular neural networks with delays and reaction-diffusion terms. By constructing a suitable Lyapunov functional and utilizing some inequality techniques, we obtain a sufficient condition for the uniqueness and global exponential stability of the equilibrium solution for a class of fuzzy cellular neural networks with delays and reaction-diffusion terms. The result imposes constraint conditions on the network parameters independently of the delay parameter. The result is also easy to check and plays an important role in the design and application of globally exponentially stable fuzzy neural circuits

  10. Cellular reprogramming through mitogen-activated protein kinases

    Directory of Open Access Journals (Sweden)

    Justin eLee

    2015-10-01

    Full Text Available Mitogen-activated protein kinase (MAPK cascades are conserved eukaryote signaling modules where MAPKs, as the final kinases in the cascade, phosphorylate protein substrates to regulate cellular processes. While some progress in the identification of MAPK substrates has been made in plants, the knowledge on the spectrum of substrates and their mechanistic action is still fragmentary. In this focused review, we discuss the biological implications of the data in our original paper (Sustained mitogen-activated protein kinase activation reprograms defense metabolism and phosphoprotein profile in Arabidopsis thaliana; Frontiers in Plant Science 5: 554 in the context of related research. In our work, we mimicked in vivo activation of two stress-activated MAPKs, MPK3 and MPK6, through transgenic manipulation of Arabidopsis thaliana and used phosphoproteomics analysis to identify potential novel MAPK substrates. Here, we plotted the identified putative MAPK substrates (and downstream phosphoproteins as a global protein clustering network. Based on a highly stringent selection confidence level, the core networks highlighted a MAPK-induced cellular reprogramming at multiple levels of gene and protein expression – including transcriptional, post-transcriptional, translational, post-translational (such as protein modification, folding and degradation steps, and also protein re-compartmentalization. Additionally, the increase in putative substrates/phosphoproteins of energy metabolism and various secondary metabolite biosynthesis pathways coincides with the observed accumulation of defense antimicrobial substances as detected by metabolome analysis. Furthermore, detection of protein networks in phospholipid or redox elements suggests activation of downstream signaling events. Taken in context with other studies, MAPKs are key regulators that reprogram cellular events to orchestrate defense signaling in eukaryotes.

  11. Device-to-Device Underlay Cellular Networks with Uncertain Channel State Information

    KAUST Repository

    Memmi, Amen

    2016-01-06

    Device-to-Device (D2D) communications underlying the cellular infrastructure is a technology that has recently been proposed as a promising solution to enhance cellular network capabilities: It improves spectrum utilization, overall throughput and energy efficiency while enabling new peer-to-peer and location-based applications and services. However, interference is the major challenge since the same resources are shared by both systems. Therefore, interference management techniques are required to keep the interference under control. In this work, in order to mitigate interference, we consider centralized and distributed power control algorithms in a one-cell random network model. Differently from previous works, we are assuming that the channel state information (CSI) may be imperfect and include estimation errors. We evaluate how this uncertainty impacts performances.

  12. Analyzing the impact of relay station characteristics on uplink performance in cellular network

    NARCIS (Netherlands)

    Dimitrova, D.C.; van den Berg, Hans Leo; Heijenk, Geert

    2009-01-01

    Uplink users in cellular networks, such as UMTS/ HSPA, located at the edge of the cell generally suffer from poor channel conditions. Deploying intermediate relay nodes is seen as a promising approach towards extending cell coverage. This paper focuses on the role of packet scheduling in cellular

  13. Cellular Interrogation: Exploiting Cell-to-Cell Variability to Discriminate Regulatory Mechanisms in Oscillatory Signalling.

    Science.gov (United States)

    Estrada, Javier; Andrew, Natalie; Gibson, Daniel; Chang, Frederick; Gnad, Florian; Gunawardena, Jeremy

    2016-07-01

    The molecular complexity within a cell may be seen as an evolutionary response to the external complexity of the cell's environment. This suggests that the external environment may be harnessed to interrogate the cell's internal molecular architecture. Cells, however, are not only nonlinear and non-stationary, but also exhibit heterogeneous responses within a clonal, isogenic population. In effect, each cell undertakes its own experiment. Here, we develop a method of cellular interrogation using programmable microfluidic devices which exploits the additional information present in cell-to-cell variation, without requiring model parameters to be fitted to data. We focussed on Ca2+ signalling in response to hormone stimulation, which exhibits oscillatory spiking in many cell types and chose eight models of Ca2+ signalling networks which exhibit similar behaviour in simulation. We developed a nonlinear frequency analysis for non-stationary responses, which could classify models into groups under parameter variation, but found that this question alone was unable to distinguish critical feedback loops. We further developed a nonlinear amplitude analysis and found that the combination of both questions ruled out six of the models as inconsistent with the experimentally-observed dynamics and heterogeneity. The two models that survived the double interrogation were mathematically different but schematically identical and yielded the same unexpected predictions that we confirmed experimentally. Further analysis showed that subtle mathematical details can markedly influence non-stationary responses under parameter variation, emphasising the difficulty of finding a "correct" model. By developing questions for the pathway being studied, and designing more versatile microfluidics, cellular interrogation holds promise as a systematic strategy that can complement direct intervention by genetics or pharmacology.

  14. Power Control for D2D Underlay Cellular Networks with Imperfect CSI

    KAUST Repository

    Memmi, Amen

    2017-02-09

    Device-to-Device communications underlying the cellular infrastructure is a technology that has recently been proposed as a promising solution to enhance cellular network capabilities. However, interference is the major challenge since the same resources are shared by both systems. Therefore, interference management techniques are required to keep the interference under control. In this work, in order to mitigate interference, we consider centralized and distributed power control algorithms in a one-cell random network model. Differently from previous works, we are assuming that the channel state information may be imperfect and include estimation errors. We evaluate how this uncertainty impacts performances. In the centralized approach, we derive the optimal powers that maximize the coverage probability and the rate of the cellular user while scheduling as many D2D links as possible. These powers are computed at the base station (BS) and then delivered to the users, and hence the name

  15. An Asynchronous Recurrent Network of Cellular Automaton-Based Neurons and Its Reproduction of Spiking Neural Network Activities.

    Science.gov (United States)

    Matsubara, Takashi; Torikai, Hiroyuki

    2016-04-01

    Modeling and implementation approaches for the reproduction of input-output relationships in biological nervous tissues contribute to the development of engineering and clinical applications. However, because of high nonlinearity, the traditional modeling and implementation approaches encounter difficulties in terms of generalization ability (i.e., performance when reproducing an unknown data set) and computational resources (i.e., computation time and circuit elements). To overcome these difficulties, asynchronous cellular automaton-based neuron (ACAN) models, which are described as special kinds of cellular automata that can be implemented as small asynchronous sequential logic circuits have been proposed. This paper presents a novel type of such ACAN and a theoretical analysis of its excitability. This paper also presents a novel network of such neurons, which can mimic input-output relationships of biological and nonlinear ordinary differential equation model neural networks. Numerical analyses confirm that the presented network has a higher generalization ability than other major modeling and implementation approaches. In addition, Field-Programmable Gate Array-implementations confirm that the presented network requires lower computational resources.

  16. Information flow in a network of dispersed signalers-receivers

    Science.gov (United States)

    Halupka, Konrad

    2017-11-01

    I consider a stochastic model of multi-agent communication in regular network. The model describes how dispersed animals exchange information. Each agent can initiate and transfer the signal to its nearest neighbors, who may pass it farther. For an external observer of busy networks, signaling activity may appear random, even though information flow actually thrives. Only when signal initiation and transfer are at low levels do spatiotemporal autocorrelations emerge as clumping signaling activity in space and pink noise time series. Under such conditions, the costs of signaling are moderate, but the signaler can reach a large audience. I propose that real-world networks of dispersed signalers-receivers may self-organize into this state and the flow of information maintains their integrity.

  17. Reconstruction and signal propagation analysis of the Syk signaling network in breast cancer cells.

    Directory of Open Access Journals (Sweden)

    Aurélien Naldi

    2017-03-01

    Full Text Available The ability to build in-depth cell signaling networks from vast experimental data is a key objective of computational biology. The spleen tyrosine kinase (Syk protein, a well-characterized key player in immune cell signaling, was surprisingly first shown by our group to exhibit an onco-suppressive function in mammary epithelial cells and corroborated by many other studies, but the molecular mechanisms of this function remain largely unsolved. Based on existing proteomic data, we report here the generation of an interaction-based network of signaling pathways controlled by Syk in breast cancer cells. Pathway enrichment of the Syk targets previously identified by quantitative phospho-proteomics indicated that Syk is engaged in cell adhesion, motility, growth and death. Using the components and interactions of these pathways, we bootstrapped the reconstruction of a comprehensive network covering Syk signaling in breast cancer cells. To generate in silico hypotheses on Syk signaling propagation, we developed a method allowing to rank paths between Syk and its targets. We first annotated the network according to experimental datasets. We then combined shortest path computation with random walk processes to estimate the importance of individual interactions and selected biologically relevant pathways in the network. Molecular and cell biology experiments allowed to distinguish candidate mechanisms that underlie the impact of Syk on the regulation of cortactin and ezrin, both involved in actin-mediated cell adhesion and motility. The Syk network was further completed with the results of our biological validation experiments. The resulting Syk signaling sub-networks can be explored via an online visualization platform.

  18. Network-Coded Content Delivery in Femtocaching-Assisted Cellular Networks

    KAUST Repository

    Shnaiwer, Yousef N.; Sorour, Sameh; Aboutorab, Neda; Sadeghi, Parastoo; Al-Naffouri, Tareq Y.

    2015-01-01

    Next-generation cellular networks are expected to be assisted by femtocaches (FCs), which collectively store the most popular files for the clients. Given any arbitrary non-fragmented placement of such files, a strict no-latency constraint, and clients' prior knowledge, new file download requests could be efficiently handled by both the FCs and the macrocell base station (MBS) using opportunistic network coding (ONC). In this paper, we aim to find the best allocation of coded file downloads to the FCs so as to minimize the MBS involvement in this download process. We first formulate this optimization problem over an ONC graph, and show that it is NP-hard. We then propose a greedy approach that maximizes the number of files downloaded by the FCs, with the goal to reduce the download share of the MBS. This allocation is performed using a dual conflict ONC graph to avoid conflicts among the FC downloads. Simulations show that our proposed scheme almost achieves the optimal performance and significantly saves on the MBS bandwidth.

  19. Network-Coded Content Delivery in Femtocaching-Assisted Cellular Networks

    KAUST Repository

    Shnaiwer, Yousef N.

    2015-12-06

    Next-generation cellular networks are expected to be assisted by femtocaches (FCs), which collectively store the most popular files for the clients. Given any arbitrary non-fragmented placement of such files, a strict no-latency constraint, and clients\\' prior knowledge, new file download requests could be efficiently handled by both the FCs and the macrocell base station (MBS) using opportunistic network coding (ONC). In this paper, we aim to find the best allocation of coded file downloads to the FCs so as to minimize the MBS involvement in this download process. We first formulate this optimization problem over an ONC graph, and show that it is NP-hard. We then propose a greedy approach that maximizes the number of files downloaded by the FCs, with the goal to reduce the download share of the MBS. This allocation is performed using a dual conflict ONC graph to avoid conflicts among the FC downloads. Simulations show that our proposed scheme almost achieves the optimal performance and significantly saves on the MBS bandwidth.

  20. Modeling cellular networks in fading environments with dominant specular components

    KAUST Repository

    AlAmmouri, Ahmad

    2016-07-26

    Stochastic geometry (SG) has been widely accepted as a fundamental tool for modeling and analyzing cellular networks. However, the fading models used with SG analysis are mainly confined to the simplistic Rayleigh fading, which is extended to the Nakagami-m fading in some special cases. However, neither the Rayleigh nor the Nakagami-m accounts for dominant specular components (DSCs) which may appear in realistic fading channels. In this paper, we present a tractable model for cellular networks with generalized two-ray (GTR) fading channel. The GTR fading explicitly accounts for two DSCs in addition to the diffuse components and offers high flexibility to capture diverse fading channels that appear in realistic outdoor/indoor wireless communication scenarios. It also encompasses the famous Rayleigh and Rician fading as special cases. To this end, the prominent effect of DSCs is highlighted in terms of average spectral efficiency. © 2016 IEEE.

  1. Universal Intelligent Small Cell (UnISCell for next generation cellular networks

    Directory of Open Access Journals (Sweden)

    Mohammad Patwary

    2016-11-01

    Full Text Available Exploring innovative cellular architectures to achieve enhanced system capacity and good coverage has become a critical issue towards realizing the next generation of wireless communications. In this context, this paper proposes a novel concept of Universal Intelligent Small Cell (UnISCell for enabling the densification of the next generation of cellular networks. The proposed novel concept envisions an integrated platform of providing a strong linkage between different stakeholders such as street lighting networks, landline telephone networks and future wireless networks, and is universal in nature being independent of the operating frequency bands and traffic types. The main motivating factors for the proposed small cell concept are the need of public infrastructure re-engineering, and the recent advances in several enabling technologies. First, we highlight the main concepts of the proposed UnISCell platform. Subsequently, we present two deployment scenarios for the proposed UnISCell concept considering infrastructure sharing and service sharing as important aspects. We then describe the key future technologies for enabling the proposed UnISCell concept and present a use case example with the help of numerical results. Finally, we conclude this article by providing some interesting future recommendations.

  2. Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information

    Directory of Open Access Journals (Sweden)

    Lemke Ney

    2009-09-01

    Full Text Available Abstract Background The identification of essential genes is important for the understanding of the minimal requirements for cellular life and for practical purposes, such as drug design. However, the experimental techniques for essential genes discovery are labor-intensive and time-consuming. Considering these experimental constraints, a computational approach capable of accurately predicting essential genes would be of great value. We therefore present here a machine learning-based computational approach relying on network topological features, cellular localization and biological process information for prediction of essential genes. Results We constructed a decision tree-based meta-classifier and trained it on datasets with individual and grouped attributes-network topological features, cellular compartments and biological processes-to generate various predictors of essential genes. We showed that the predictors with better performances are those generated by datasets with integrated attributes. Using the predictor with all attributes, i.e., network topological features, cellular compartments and biological processes, we obtained the best predictor of essential genes that was then used to classify yeast genes with unknown essentiality status. Finally, we generated decision trees by training the J48 algorithm on datasets with all network topological features, cellular localization and biological process information to discover cellular rules for essentiality. We found that the number of protein physical interactions, the nuclear localization of proteins and the number of regulating transcription factors are the most important factors determining gene essentiality. Conclusion We were able to demonstrate that network topological features, cellular localization and biological process information are reliable predictors of essential genes. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing

  3. PATHLOGIC-S: a scalable Boolean framework for modelling cellular signalling.

    Directory of Open Access Journals (Sweden)

    Liam G Fearnley

    Full Text Available Curated databases of signal transduction have grown to describe several thousand reactions, and efficient use of these data requires the development of modelling tools to elucidate and explore system properties. We present PATHLOGIC-S, a Boolean specification for a signalling model, with its associated GPL-licensed implementation using integer programming techniques. The PATHLOGIC-S specification has been designed to function on current desktop workstations, and is capable of providing analyses on some of the largest currently available datasets through use of Boolean modelling techniques to generate predictions of stable and semi-stable network states from data in community file formats. PATHLOGIC-S also addresses major problems associated with the presence and modelling of inhibition in Boolean systems, and reduces logical incoherence due to common inhibitory mechanisms in signalling systems. We apply this approach to signal transduction networks including Reactome and two pathways from the Panther Pathways database, and present the results of computations on each along with a discussion of execution time. A software implementation of the framework and model is freely available under a GPL license.

  4. Almost sure exponential stability of stochastic fuzzy cellular neural networks with delays

    International Nuclear Information System (INIS)

    Zhao Hongyong; Ding Nan; Chen Ling

    2009-01-01

    This paper is concerned with the problem of exponential stability analysis for fuzzy cellular neural network with delays. By constructing suitable Lyapunov functional and using stochastic analysis we present some sufficient conditions ensuring almost sure exponential stability for the network. Moreover, an example is given to demonstrate the advantages of our method.

  5. 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.

  6. Linear matrix inequality approach for synchronization control of fuzzy cellular neural networks with mixed time delays

    International Nuclear Information System (INIS)

    Balasubramaniam, P.; Kalpana, M.; Rakkiyappan, R.

    2012-01-01

    Fuzzy cellular neural networks (FCNNs) are special kinds of cellular neural networks (CNNs). Each cell in an FCNN contains fuzzy operating abilities. The entire network is governed by cellular computing laws. The design of FCNNs is based on fuzzy local rules. In this paper, a linear matrix inequality (LMI) approach for synchronization control of FCNNs with mixed delays is investigated. Mixed delays include discrete time-varying delays and unbounded distributed delays. A dynamic control scheme is proposed to achieve the synchronization between a drive network and a response network. By constructing the Lyapunov—Krasovskii functional which contains a triple-integral term and the free-weighting matrices method an improved delay-dependent stability criterion is derived in terms of LMIs. The controller can be easily obtained by solving the derived LMIs. A numerical example and its simulations are presented to illustrate the effectiveness of the proposed method. (interdisciplinary physics and related areas of science and technology)

  7. Synchronization transmission of laser pattern signal within uncertain switched network

    Science.gov (United States)

    Lü, Ling; Li, Chengren; Li, Gang; Sun, Ao; Yan, Zhe; Rong, Tingting; Gao, Yan

    2017-06-01

    We propose a new technology for synchronization transmission of laser pattern signal within uncertain network with controllable topology. In synchronization process, the connection of dynamic network can vary at all time according to different demands. Especially, we construct the Lyapunov function of network through designing a special semi-positive definite function, and the synchronization transmission of laser pattern signal within uncertain network with controllable topology can be realized perfectly, which effectively avoids the complicated calculation for solving the second largest eignvalue of the coupling matrix of the dynamic network in order to obtain the network synchronization condition. At the same time, the uncertain parameters in dynamic equations belonging to network nodes can also be identified accurately via designing the identification laws of uncertain parameters. In addition, there are not any limitations for the synchronization target of network in the new technology, in other words, the target can either be a state variable signal of an arbitrary node within the network or an exterior signal.

  8. Assessing the weather monitoring capabilities of cellular microwave link networks

    Science.gov (United States)

    Fencl, Martin; Vrzba, Miroslav; Rieckermann, Jörg; Bareš, Vojtěch

    2016-04-01

    Using of microwave links for rainfall monitoring was suggested already by (Atlas and Ulbrich, 1977). However, this technique attracted broader attention of scientific community only in the recent decade, with the extensive growth of cellular microwave link (CML) networks, which form the backbone of today's cellular telecommunication infrastructure. Several studies have already shown that CMLs can be conveniently used as weather sensors and have potential to provide near-ground path-integrated observations of rainfall but also humidity or fog. However, although research is still focusing on algorithms to improve the weather sensing capabilities (Fencl et al., 2015), it is not clear how to convince cellular operators to provide the power levels of their network. One step in this direction is to show in which regions or municipalities the networks are sufficiently dense to provide/develop good services. In this contribution we suggest a standardized approach to evaluate CML networks in terms of rainfall observation and to identify suitable regions for CML rainfall monitoring. We estimate precision of single CML based on its sensitivity to rainfall, i.e. as a function of frequency, polarization and path length. Capability of a network to capture rainfall spatial patterns is estimated from the CML coverage and path lengths considering that single CML provides path-integrated rain rates. We also search for suitable predictors for regions where no network topologies are available. We test our approach on several European networks and discuss the results. Our results show that CMLs are very dense in urban areas (> 1 CML/km2), but less in rural areas (online tool. In summary, our results demonstrate that CML represent promising environmental observation network, suitable especially for urban rainfall monitoring. The developed approach integrated into an open source online tool can be conveniently used e.g. by local operators or authorities to evaluate the suitability of

  9. Mobility-Aware Modeling and Analysis of Dense Cellular Networks With $C$ -Plane/ $U$ -Plane Split Architecture

    KAUST Repository

    Ibrahim, Hazem

    2016-09-19

    The unrelenting increase in the population of mobile users and their traffic demands drive cellular network operators to densify their network infrastructure. Network densification shrinks the footprint of base stations (BSs) and reduces the number of users associated with each BS, leading to an improved spatial frequency reuse and spectral efficiency, and thus, higher network capacity. However, the densification gain comes at the expense of higher handover rates and network control overhead. Hence, user’s mobility can diminish or even nullifies the foreseen densification gain. In this context, splitting the control plane ( C -plane) and user plane ( U -plane) is proposed as a potential solution to harvest densification gain with reduced cost in terms of handover rate and network control overhead. In this paper, we use stochastic geometry to develop a tractable mobility-aware model for a two-tier downlink cellular network with ultra-dense small cells and C -plane/ U -plane split architecture. The developed model is then used to quantify the effect of mobility on the foreseen densification gain with and without C -plane/ U -plane split. To this end, we shed light on the handover problem in dense cellular environments, show scenarios where the network fails to support certain mobility profiles, and obtain network design insights.

  10. Analysis and logical modeling of biological signaling transduction networks

    Science.gov (United States)

    Sun, Zhongyao

    The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

  11. Rapidly exploring structural and dynamic properties of signaling networks using PathwayOracle

    Directory of Open Access Journals (Sweden)

    Ram Prahlad T

    2008-08-01

    Full Text Available Abstract Background In systems biology the experimentalist is presented with a selection of software for analyzing dynamic properties of signaling networks. These tools either assume that the network is in steady-state or require highly parameterized models of the network of interest. For biologists interested in assessing how signal propagates through a network under specific conditions, the first class of methods does not provide sufficiently detailed results and the second class requires models which may not be easily and accurately constructed. A tool that is able to characterize the dynamics of a signaling network using an unparameterized model of the network would allow biologists to quickly obtain insights into a signaling network's behavior. Results We introduce PathwayOracle, an integrated suite of software tools for computationally inferring and analyzing structural and dynamic properties of a signaling network. The feature which differentiates PathwayOracle from other tools is a method that can predict the response of a signaling network to various experimental conditions and stimuli using only the connectivity of the signaling network. Thus signaling models are relatively easy to build. The method allows for tracking signal flow in a network and comparison of signal flows under different experimental conditions. In addition, PathwayOracle includes tools for the enumeration and visualization of coherent and incoherent signaling paths between proteins, and for experimental analysis – loading and superimposing experimental data, such as microarray intensities, on the network model. Conclusion PathwayOracle provides an integrated environment in which both structural and dynamic analysis of a signaling network can be quickly conducted and visualized along side experimental results. By using the signaling network connectivity, analyses and predictions can be performed quickly using relatively easily constructed signaling network models

  12. 5G and Cellular Networks in the Smart Grid

    DEFF Research Database (Denmark)

    Nielsen, Jimmy Jessen; Jorguseski, Ljupco; Zhang, Haibin

    2018-01-01

    grid. In the present chapter, we present the main features of both the non-3GPP technologies, IEEE 802.11ah, SigFox and LoRa, and the main features of past, current and future 3GPP technologies, namely releases High rate), 12-14 (IoT extensions) and 15-16 (5G). Additionally, we present......Wireless cellular networks will help Distribution System Operators (DSOs) to achieve observability below the substation level, which is needed to ensure stable operation in the smart grid. Both existing and upcoming cellular technologies are considered as candidates for helping to enable the smart...... the challenges and possible solutions for ensuring end-to-end security in smart grid systems....

  13. Mechanotransduction and Growth Factor Signalling to Engineer Cellular Microenvironments.

    Science.gov (United States)

    Cipitria, Amaia; Salmeron-Sanchez, Manuel

    2017-08-01

    Engineering cellular microenvironments involves biochemical factors, the extracellular matrix (ECM) and the interaction with neighbouring cells. This progress report provides a critical overview of key studies that incorporate growth factor (GF) signalling and mechanotransduction into the design of advanced microenvironments. Materials systems have been developed for surface-bound presentation of GFs, either covalently tethered or sequestered through physico-chemical affinity to the matrix, as an alternative to soluble GFs. Furthermore, some materials contain both GF and integrin binding regions and thereby enable synergistic signalling between the two. Mechanotransduction refers to the ability of the cells to sense physical properties of the ECM and to transduce them into biochemical signals. Various aspects of the physics of the ECM, i.e. stiffness, geometry and ligand spacing, as well as time-dependent properties, such as matrix stiffening, degradability, viscoelasticity, surface mobility as well as spatial patterns and gradients of physical cues are discussed. To conclude, various examples illustrate the potential for cooperative signalling of growth factors and the physical properties of the microenvironment for potential applications in regenerative medicine, cancer research and drug testing. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Identification of driving network of cellular differentiation from single sample time course gene expression data

    Science.gov (United States)

    Chen, Ye; Wolanyk, Nathaniel; Ilker, Tunc; Gao, Shouguo; Wang, Xujing

    Methods developed based on bifurcation theory have demonstrated their potential in driving network identification for complex human diseases, including the work by Chen, et al. Recently bifurcation theory has been successfully applied to model cellular differentiation. However, there one often faces a technical challenge in driving network prediction: time course cellular differentiation study often only contains one sample at each time point, while driving network prediction typically require multiple samples at each time point to infer the variation and interaction structures of candidate genes for the driving network. In this study, we investigate several methods to identify both the critical time point and the driving network through examination of how each time point affects the autocorrelation and phase locking. We apply these methods to a high-throughput sequencing (RNA-Seq) dataset of 42 subsets of thymocytes and mature peripheral T cells at multiple time points during their differentiation (GSE48138 from GEO). We compare the predicted driving genes with known transcription regulators of cellular differentiation. We will discuss the advantages and limitations of our proposed methods, as well as potential further improvements of our methods.

  15. Valuing spectrum at mm wavelengths for cellular networks

    OpenAIRE

    Shaw, B. A.; Beltrán, H. F.; Sowerby, K. W.

    2017-01-01

    This paper investigates the economic value of spectrum at mm wavelengths. The analysis uses four techniques to value spectrum, namely a benchmarking comparison, a discounted cash flow analysis, a real options approach and a deprival method. The methods to calculate spectrum value presented in this paper can be used for any spectrum band and in any country. However, to determine the value of mm wavelengths for cellular networks, we have used data from New Zealand, specifically for the existing...

  16. Stochastic Geometric Coverage Analysis in mmWave Cellular Networks with a Realistic Channel Model

    DEFF Research Database (Denmark)

    Rebato, Mattia; Park, Jihong; Popovski, Petar

    2017-01-01

    Millimeter-wave (mmWave) bands have been attracting growing attention as a possible candidate for next-generation cellular networks, since the available spectrum is orders of magnitude larger than in current cellular allocations. To precisely design mmWave systems, it is important to examine mmWa...

  17. Detection test of wireless network signal strength and GPS positioning signal in underground pipeline

    Science.gov (United States)

    Li, Li; Zhang, Yunwei; Chen, Ling

    2018-03-01

    In order to solve the problem of selecting positioning technology for inspection robot in underground pipeline environment, the wireless network signal strength and GPS positioning signal testing are carried out in the actual underground pipeline environment. Firstly, the strength variation of the 3G wireless network signal and Wi-Fi wireless signal provided by China Telecom and China Unicom ground base stations are tested, and the attenuation law of these wireless signals along the pipeline is analyzed quantitatively and described. Then, the receiving data of the GPS satellite signal in the pipeline are tested, and the attenuation of GPS satellite signal under underground pipeline is analyzed. The testing results may be reference for other related research which need to consider positioning in pipeline.

  18. Modelling the structure of a ceRNA-theoretical, bipartite microRNA-mRNA interaction network regulating intestinal epithelial cellular pathways using R programming.

    Science.gov (United States)

    Robinson, J M; Henderson, W A

    2018-01-12

    We report a method using functional-molecular databases and network modelling to identify hypothetical mRNA-miRNA interaction networks regulating intestinal epithelial barrier function. The model forms a data-analysis component of our cell culture experiments, which produce RNA expression data from Nanostring Technologies nCounter ® system. The epithelial tight-junction (TJ) and actin cytoskeleton interact as molecular components of the intestinal epithelial barrier. Upstream regulation of TJ-cytoskeleton interaction is effected by the Rac/Rock/Rho signaling pathway and other associated pathways which may be activated or suppressed by extracellular signaling from growth factors, hormones, and immune receptors. Pathway activations affect epithelial homeostasis, contributing to degradation of the epithelial barrier associated with osmotic dysregulation, inflammation, and tumor development. The complexity underlying miRNA-mRNA interaction networks represents a roadblock for prediction and validation of competing-endogenous RNA network function. We developed a network model to identify hypothetical co-regulatory motifs in a miRNA-mRNA interaction network related to epithelial function. A mRNA-miRNA interaction list was generated using KEGG and miRWalk2.0 databases. R-code was developed to quantify and visualize inherent network structures. We identified a sub-network with a high number of shared, targeting miRNAs, of genes associated with cellular proliferation and cancer, including c-MYC and Cyclin D.

  19. Flexible Design for α-Duplex Communications in Multi-Tier Cellular Networks

    KAUST Repository

    Alammouri, Ahmad; Elsawy, Hesham; Alouini, Mohamed-Slim

    2016-01-01

    the foreseen FD gains. This paper presents flexible and tractable modeling framework for multi-tier cellular networks with FD BSs and FD/HD UEs. The presented model is based on stochastic geometry and accounts for the intrinsic vulnerability of uplink

  20. Cellular neural networks, the Navier-Stokes equation, and microarray image reconstruction.

    Science.gov (United States)

    Zineddin, Bachar; Wang, Zidong; Liu, Xiaohui

    2011-11-01

    Although the last decade has witnessed a great deal of improvements achieved for the microarray technology, many major developments in all the main stages of this technology, including image processing, are still needed. Some hardware implementations of microarray image processing have been proposed in the literature and proved to be promising alternatives to the currently available software systems. However, the main drawback of those proposed approaches is the unsuitable addressing of the quantification of the gene spot in a realistic way without any assumption about the image surface. Our aim in this paper is to present a new image-reconstruction algorithm using the cellular neural network that solves the Navier-Stokes equation. This algorithm offers a robust method for estimating the background signal within the gene-spot region. The MATCNN toolbox for Matlab is used to test the proposed method. Quantitative comparisons are carried out, i.e., in terms of objective criteria, between our approach and some other available methods. It is shown that the proposed algorithm gives highly accurate and realistic measurements in a fully automated manner within a remarkably efficient time.

  1. Decoding signalling networks by mass spectrometry-based proteomics

    DEFF Research Database (Denmark)

    Choudhary, Chuna Ram; Mann, Matthias

    2010-01-01

    Signalling networks regulate essentially all of the biology of cells and organisms in normal and disease states. Signalling is often studied using antibody-based techniques such as western blots. Large-scale 'precision proteomics' based on mass spectrometry now enables the system......-wide characterization of signalling events at the levels of post-translational modifications, protein-protein interactions and changes in protein expression. This technology delivers accurate and unbiased information about the quantitative changes of thousands of proteins and their modifications in response to any...... perturbation. Current studies focus on phosphorylation, but acetylation, methylation, glycosylation and ubiquitylation are also becoming amenable to investigation. Large-scale proteomics-based signalling research will fundamentally change our understanding of signalling networks....

  2. Mobility-Aware User Association in Uplink Cellular Networks

    KAUST Repository

    Arshad, Rabe; Elsawy, Hesham; Sorour, Sameh; Alouini, Mohamed-Slim; Al-Naffouri, Tareq Y.

    2017-01-01

    This letter studies the mobility aware user-to-BS association policies, within a stochastic geometry framework, in two tier uplink cellular networks with fractional channel inversion power control. Particularly, we model the base stations’ locations using the widely accepted poisson point process and obtain the coverage probability and handover cost expressions for the coupled and decoupled uplink and downlink associations. To this end, we compute the average throughput for the mobile users and study the merits and demerits of each association strategy.

  3. Mobility-Aware User Association in Uplink Cellular Networks

    KAUST Repository

    Arshad, Rabe

    2017-07-20

    This letter studies the mobility aware user-to-BS association policies, within a stochastic geometry framework, in two tier uplink cellular networks with fractional channel inversion power control. Particularly, we model the base stations’ locations using the widely accepted poisson point process and obtain the coverage probability and handover cost expressions for the coupled and decoupled uplink and downlink associations. To this end, we compute the average throughput for the mobile users and study the merits and demerits of each association strategy.

  4. Cellular telephone-based wide-area radiation detection network

    Science.gov (United States)

    Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

    2009-06-09

    A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

  5. Mobility-Aware Modeling and Analysis of Dense Cellular Networks With $C$ -Plane/ $U$ -Plane Split Architecture

    KAUST Repository

    Ibrahim, Hazem; Elsawy, Hesham; Nguyen, Uyen Trang; Alouini, Mohamed-Slim

    2016-01-01

    The unrelenting increase in the population of mobile users and their traffic demands drive cellular network operators to densify their network infrastructure. Network densification shrinks the footprint of base stations (BSs) and reduces the number

  6. Prioritizing Signaling Information Transmission in Next Generation Networks

    Directory of Open Access Journals (Sweden)

    Jasmina Baraković

    2011-01-01

    Full Text Available Next generation transport network is characterized by the use of in-band signaling, where Internet Protocol (IP packets carrying signaling or media information are mixed in transmission. Since transport resources are limited, when any segment of access or core network is congested, IP packets carrying signaling information may be discarded. As a consequence, it may be impossible to implement reachability and quality of service (QoS. Since present approaches are insufficient to completely address this problem, a novel approach is proposed, which is based on prioritizing signaling information transmission. To proof the concept, a simulation study was performed using Network Simulator version 2 (ns-2 and independently developed Session Initiation Protocol (SIP module. The obtained results were statistically processed using Statistical Package for the Social Sciences (SPSS version 15.0. Summarizing our research results, several issues are identified for future work.

  7. All-optical network coding for DPSK signals

    DEFF Research Database (Denmark)

    An, Yi; Da Ros, Francesco; Peucheret, Christophe

    2013-01-01

    All-optical network coding for path protection is experimentally demonstrated using four-wave mixing in SOAs for10 Gbit/s NRZ-DPSK signals with error free performance. The total power penalty after two cascaded XOR stage is only 2 dB.......All-optical network coding for path protection is experimentally demonstrated using four-wave mixing in SOAs for10 Gbit/s NRZ-DPSK signals with error free performance. The total power penalty after two cascaded XOR stage is only 2 dB....

  8. A Neural Network based Approach for Predicting Customer Churn in Cellular Network Services

    OpenAIRE

    Sharma, Anuj; Panigrahi, Dr. Prabin Kumar

    2013-01-01

    Marketing literature states that it is more costly to engage a new customer than to retain an existing loyal customer. Churn prediction models are developed by academics and practitioners to effectively manage and control customer churn in order to retain existing customers. As churn management is an important activity for companies to retain loyal customers, the ability to correctly predict customer churn is necessary. As the cellular network services market becoming more competitive, custom...

  9. Exponential convergence for a class of delayed cellular neural networks with time-varying coefficients

    International Nuclear Information System (INIS)

    Liu Bingwen

    2008-01-01

    In this Letter, we consider a class of delayed cellular neural networks with time-varying coefficients. By applying Lyapunov functional method and differential inequality techniques, we establish new results to ensure that all solutions of the networks converge exponentially to zero point

  10. Exploratory Analysis of a GGSN’s PDP Context Signaling Load

    Directory of Open Access Journals (Sweden)

    Florian Metzger

    2014-01-01

    Full Text Available This paper takes an exploratory look on control plane signaling in a mobile cellular core network. In contrast to most contributions in this field, our focus does not lie on the wireless or user-oriented parts of the network, but on signaling in the core network. In an investigation of core network data we take a look at statistics related to GTP tunnels and their signaling. Based on the results thereof we propose a definition of load at the GGSN and create an initial load queuing model. We find signs of user devices putting burden on the core network through their behavior.

  11. Cellular Neural Network-Based Methods for Distributed Network Intrusion Detection

    Directory of Open Access Journals (Sweden)

    Kang Xie

    2015-01-01

    Full Text Available According to the problems of current distributed architecture intrusion detection systems (DIDS, a new online distributed intrusion detection model based on cellular neural network (CNN was proposed, in which discrete-time CNN (DTCNN was used as weak classifier in each local node and state-controlled CNN (SCCNN was used as global detection method, respectively. We further proposed a new method for design template parameters of SCCNN via solving Linear Matrix Inequality. Experimental results based on KDD CUP 99 dataset show its feasibility and effectiveness. Emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI implementation which allows the distributed intrusion detection to be performed better.

  12. Modeling evolution of crosstalk in noisy signal transduction networks

    Science.gov (United States)

    Tareen, Ammar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

    2018-02-01

    Signal transduction networks can form highly interconnected systems within cells due to crosstalk between constituent pathways. To better understand the evolutionary design principles underlying such networks, we study the evolution of crosstalk for two parallel signaling pathways that arise via gene duplication. We use a sequence-based evolutionary algorithm and evolve the network based on two physically motivated fitness functions related to information transmission. We find that one fitness function leads to a high degree of crosstalk while the other leads to pathway specificity. Our results offer insights on the relationship between network architecture and information transmission for noisy biomolecular networks.

  13. In-Band α-Duplex Scheme for Cellular Networks: A Stochastic Geometry Approach

    KAUST Repository

    Alammouri, Ahmad; Elsawy, Hesham; Amin, Osama; Alouini, Mohamed-Slim

    2016-01-01

    In-band full-duplex (FD) communications have been optimistically promoted to improve the spectrum utilization and efficiency. However, the penetration of FD communications to the cellular networks domain is challenging due to the imposed uplink

  14. Fiber fault location utilizing traffic signal in optical network.

    Science.gov (United States)

    Zhao, Tong; Wang, Anbang; Wang, Yuncai; Zhang, Mingjiang; Chang, Xiaoming; Xiong, Lijuan; Hao, Yi

    2013-10-07

    We propose and experimentally demonstrate a method for fault location in optical communication network. This method utilizes the traffic signal transmitted across the network as probe signal, and then locates the fault by correlation technique. Compared with conventional techniques, our method has a simple structure and low operation expenditure, because no additional device is used, such as light source, modulator and signal generator. The correlation detection in this method overcomes the tradeoff between spatial resolution and measurement range in pulse ranging technique. Moreover, signal extraction process can improve the location result considerably. Experimental results show that we achieve a spatial resolution of 8 cm and detection range of over 23 km with -8-dBm mean launched power in optical network based on synchronous digital hierarchy protocols.

  15. Dopamine D1 signaling organizes network dynamics underlying working memory.

    Science.gov (United States)

    Roffman, Joshua L; Tanner, Alexandra S; Eryilmaz, Hamdi; Rodriguez-Thompson, Anais; Silverstein, Noah J; Ho, New Fei; Nitenson, Adam Z; Chonde, Daniel B; Greve, Douglas N; Abi-Dargham, Anissa; Buckner, Randy L; Manoach, Dara S; Rosen, Bruce R; Hooker, Jacob M; Catana, Ciprian

    2016-06-01

    Local prefrontal dopamine signaling supports working memory by tuning pyramidal neurons to task-relevant stimuli. Enabled by simultaneous positron emission tomography-magnetic resonance imaging (PET-MRI), we determined whether neuromodulatory effects of dopamine scale to the level of cortical networks and coordinate their interplay during working memory. Among network territories, mean cortical D1 receptor densities differed substantially but were strongly interrelated, suggesting cross-network regulation. Indeed, mean cortical D1 density predicted working memory-emergent decoupling of the frontoparietal and default networks, which respectively manage task-related and internal stimuli. In contrast, striatal D1 predicted opposing effects within these two networks but no between-network effects. These findings specifically link cortical dopamine signaling to network crosstalk that redirects cognitive resources to working memory, echoing neuromodulatory effects of D1 signaling on the level of cortical microcircuits.

  16. Identification and analysis of signaling networks potentially involved in breast carcinoma metastasis to the brain.

    Directory of Open Access Journals (Sweden)

    Feng Li

    Full Text Available Brain is a common site of breast cancer metastasis associated with significant neurologic morbidity, decreased quality of life, and greatly shortened survival. However, the molecular and cellular mechanisms underpinning brain colonization by breast carcinoma cells are poorly understood. Here, we used 2D-DIGE (Difference in Gel Electrophoresis proteomic analysis followed by LC-tandem mass spectrometry to identify the proteins differentially expressed in brain-targeting breast carcinoma cells (MB231-Br compared with parental MDA-MB-231 cell line. Between the two cell lines, we identified 12 proteins consistently exhibiting greater than 2-fold (p<0.05 difference in expression, which were associated by the Ingenuity Pathway Analysis (IPA with two major signaling networks involving TNFα/TGFβ-, NFκB-, HSP-70-, TP53-, and IFNγ-associated pathways. Remarkably, highly related networks were revealed by the IPA analysis of a list of 19 brain-metastasis-associated proteins identified recently by the group of Dr. A. Sierra using MDA-MB-435-based experimental system (Martin et al., J Proteome Res 2008 7:908-20, or a 17-gene classifier associated with breast cancer brain relapse reported by the group of Dr. J. Massague based on a microarray analysis of clinically annotated breast tumors from 368 patients (Bos et al., Nature 2009 459: 1005-9. These findings, showing that different experimental systems and approaches (2D-DIGE proteomics used on brain targeting cell lines or gene expression analysis of patient samples with documented brain relapse yield highly related signaling networks, suggest strongly that these signaling networks could be essential for a successful colonization of the brain by metastatic breast carcinoma cells.

  17. Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

    Science.gov (United States)

    Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

    2015-11-01

    Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

  18. Network-Coded Macrocell Offloading in Femtocaching-Assisted Cellular Networks

    KAUST Repository

    Shnaiwer, Yousef; Sorour, Sameh; Sadeghi, Parastoo; Aboutorab, Neda; Al-Naffouri, Tareq Y.

    2017-01-01

    Opportunistic network coding (ONC) has shown high potential in enhancing the quality-of-experience (QoE) for the clients of cellular networks using their previously downloaded files. In this paper, we study the problem of offloading clients from the macrocell base station (MBS) with the help of femtocaches (FCs) and ONC. We formulate this MBS offloading problem as an optimization problem over an ONC graph, and prove that it is non-deterministic polynomial-time (NP)-hard. Thus, we propose an ONC-broadcast offloading scheme, which utilizes separate ONC graphs at the MBS and FCs in addition to uncoded broadcasting, to offload the clients from the MBS. We analyze the performance of the ONC-broadcast offloading scheme and show that it is asymptotically optimal using random graph theory. Since even this ONC-broadcast offloading scheme is still NP-hard to implement, we devise an efficient heuristic to simplify the implementation. We show that the proposed heuristic reduces the worst-case complexity of implementing the ONC-broadcast offloading scheme from an exponential to a quadratic function of the total number of vertices in the FC ONC graph. Simulation results show that, despite its low complexity, the proposed heuristic achieves similar MBS offloading performance to the ONC-broadcast offloading scheme.

  19. Network-Coded Macrocell Offloading in Femtocaching-Assisted Cellular Networks

    KAUST Repository

    Shnaiwer, Yousef

    2017-11-08

    Opportunistic network coding (ONC) has shown high potential in enhancing the quality-of-experience (QoE) for the clients of cellular networks using their previously downloaded files. In this paper, we study the problem of offloading clients from the macrocell base station (MBS) with the help of femtocaches (FCs) and ONC. We formulate this MBS offloading problem as an optimization problem over an ONC graph, and prove that it is non-deterministic polynomial-time (NP)-hard. Thus, we propose an ONC-broadcast offloading scheme, which utilizes separate ONC graphs at the MBS and FCs in addition to uncoded broadcasting, to offload the clients from the MBS. We analyze the performance of the ONC-broadcast offloading scheme and show that it is asymptotically optimal using random graph theory. Since even this ONC-broadcast offloading scheme is still NP-hard to implement, we devise an efficient heuristic to simplify the implementation. We show that the proposed heuristic reduces the worst-case complexity of implementing the ONC-broadcast offloading scheme from an exponential to a quadratic function of the total number of vertices in the FC ONC graph. Simulation results show that, despite its low complexity, the proposed heuristic achieves similar MBS offloading performance to the ONC-broadcast offloading scheme.

  20. Power Control for D2D Underlay Cellular Networks With Channel Uncertainty

    KAUST Repository

    Memmi, Amen

    2016-12-26

    Device-to-device (D2D) communications underlying the cellular infrastructure are a technology that have been proposed recently as a promising solution to enhance cellular network capabilities. It improves spectrum utilization, overall throughput, and energy efficiency while enabling new peer-to-peer and location-based applications and services. However, interference is the major challenge, since the same resources are shared by both systems. Therefore, interference management techniques are required to keep the interference under control. In this paper, in order to mitigate interference, we consider centralized and distributed power control algorithms in a one-cell random network model. Existing results on D2D underlay networks assume perfect channel state information (CSI). This assumption is usually unrealistic in practice due to the dynamic nature of wireless channels. Thus, it is of great interest to study and evaluate achievable performances under channel uncertainty. Differently from previous works, we are assuming that the CSI may be imperfect and include estimation errors. In the centralized approach, we derive the optimal powers that maximize the coverage probability and the rate of the cellular user while scheduling as many D2D links as possible. These powers are computed at the base station (BS) and then delivered to the users, and hence the name “centralized”. For the distributed method, the ON–OFF power control and the truncated channel inversion are proposed. Expressions of coverage probabilities are established in the function of D2D links intensity, pathloss exponent, and estimation error variance. Results show the important influence of CSI error on achievable performances and thus how crucial it is to consider it while designing networks and evaluating performances.

  1. FTIR spectroscopic studies of bacterial cellular responses to environmental factors, plant-bacterial interactions and signalling

    OpenAIRE

    Kamnev, Alexander A.

    2008-01-01

    Modern spectroscopic techniques are highly useful in studying diverse processes in microbial cells related to or incited by environmental factors. Spectroscopic data for whole cells, supramolecular structures or isolated cellular constituents can reflect structural and/or compositional changes occurring in the course of cellular metabolic responses to the effects of pollutants, environmental conditions (stress factors); nutrients, signalling molecules (communication factors), etc. This inform...

  2. Application of neural networks to signal prediction in nuclear power plant

    International Nuclear Information System (INIS)

    Wan Joo Kim; Soon Heung Chang; Byung Ho Lee

    1993-01-01

    This paper describes the feasibility study of an artificial neural network for signal prediction. The purpose of signal prediction is to estimate the value of undetected next time step signal. As the prediction method, based on the idea of auto regression, a few previous signals are inputs to the artificial neural network and the signal value of next time step is estimated with the outputs of the network. The artificial neural network can be applied to the nonlinear system and answers in short time. The training algorithm is a modified backpropagation model, which can effectively reduce the training time. The target signal of the simulation is the steam generator water level, which is one of the important parameters in nuclear power plants. The simulation result shows that the predicted value follows the real trend well

  3. Load-aware modeling for uplink cellular networks in a multi-channel environment

    KAUST Repository

    Alammouri, Ahmad; Elsawy, Hesham; Alouini, Mohamed-Slim

    2014-01-01

    We exploit tools from stochastic geometry to develop a tractable analytical approach for modeling uplink cellular networks. The developed model is load aware and accounts for per-user power control as well as the limited transmit power constraint

  4. Stability analysis of impulsive fuzzy cellular neural networks with distributed delays and reaction-diffusion terms

    International Nuclear Information System (INIS)

    Li Zuoan; Li Kelin

    2009-01-01

    In this paper, we investigate a class of impulsive fuzzy cellular neural networks with distributed delays and reaction-diffusion terms. By employing the delay differential inequality with impulsive initial conditions and M-matrix theory, we find some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for impulsive fuzzy cellular neural networks with distributed delays and reaction-diffusion terms. In particular, the estimate of the exponential converging index is also provided, which depends on the system parameters. An example is given to show the effectiveness of the results obtained here.

  5. Joint Secrecy for D2D Communications Underlying Cellular Networks

    KAUST Repository

    Hyadi, Amal

    2018-01-15

    In this work, we investigate the ergodic secrecy rate region of a block-fading spectrum-sharing system, where a D2D communication is underlying a cellular channel. We consider that both the primary and the secondary transmissions require their respective transmitted messages to be kept secret from a common eavesdropper under a joint secrecy constraint. The presented results are for three different scenarios, each corresponding to a particular requirement of the cellular system. First, we consider the case of a fair cellular system, and we show that the impact of jointly securing the transmissions can be balanced between the primary and the secondary systems. The second scenario examines the case when the primary network is demanding and requires the secondary transmission to be at a rate that is decodable by the primary receiver, while the last scenario assumes a joint transmission of artificial noise by the primary and the secondary transmitters. For each scenario, we present an achievable ergodic secrecy rate region that can be used as an indicator for the cellular and the D2D systems to agree under which terms the spectrum will be shared.

  6. In-Band α-Duplex Scheme for Cellular Networks: A Stochastic Geometry Approach

    KAUST Repository

    Alammouri, Ahmad

    2016-07-13

    In-band full-duplex (FD) communications have been optimistically promoted to improve the spectrum utilization and efficiency. However, the penetration of FD communications to the cellular networks domain is challenging due to the imposed uplink/downlink interference. This paper presents a tractable framework, based on stochastic geometry, to study FD communications in cellular networks. Particularly, we assess the FD communications effect on the network performance and quantify the associated gains. The study proves the vulnerability of the uplink to the downlink interference and shows that FD rate gains harvested in the downlink (up to 97%) come at the expense of a significant degradation in the uplink rate (up to 94%). Therefore, we propose a novel fine-grained duplexing scheme, denoted as -duplex scheme, which allows a partial overlap between the uplink and the downlink frequency bands. We derive the required conditions to harvest rate gains from the -duplex scheme and show its superiority to both the FD and half-duplex (HD) schemes. In particular, we show that the -duplex scheme provides a simultaneous improvement of 28% for the downlink rate and 56% for the uplink rate. Finally, we show that the amount of the overlap can be optimized based on the network design objective.

  7. Game-Theoretic Social-Aware Resource Allocation for Device-to-Device Communications Underlaying Cellular Network

    Directory of Open Access Journals (Sweden)

    Lei Wang

    2018-01-01

    Full Text Available Device-to-Device communication underlaying cellular network can increase the spectrum efficiency due to direct proximity communication and frequency reuse. However, such performance improvement is influenced by the power interference caused by spectrum sharing and social characteristics in each social community jointly. In this investigation, we present a dynamic game theory with complete information based D2D resource allocation scheme for D2D communication underlaying cellular network. In this resource allocation method, we quantify both the rate influence from the power interference caused by the D2D transmitter to cellular users and rate enhancement brought by the social relationships between mobile users. Then, the utility function maximization game is formulated to optimize the overall transmission rate performance of the network, which synthetically measures the final influence from both power interference and sociality enhancement. Simultaneously, we discuss the Nash Equilibrium of the proposed utility function maximization game from a theoretical point of view and further put forward a utility priority searching algorithm based resource allocation scheme. Simulation results show that our proposed scheme attains better performance compared with the other two advanced proposals.

  8. Redox modification of caveolar proteins in the cardiovascular system- role in cellular signalling and disease.

    Science.gov (United States)

    Bubb, Kristen J; Birgisdottir, Asa Birna; Tang, Owen; Hansen, Thomas; Figtree, Gemma A

    2017-08-01

    Rapid and coordinated release of a variety of reactive oxygen species (ROS) such as superoxide (O 2 .- ), hydrogen peroxide (H 2 O 2 ) and peroxynitrite, in specific microdomains, play a crucial role in cell signalling in the cardiovascular system. These reactions are mediated by reversible and functional modifications of a wide variety of key proteins. Dysregulation of this oxidative signalling occurs in almost all forms of cardiovascular disease (CVD), including at the very early phases. Despite the heavily publicized failure of "antioxidants" to improve CVD progression, pharmacotherapies such as those targeting the renin-angiotensin system, or statins, exert at least part of their large clinical benefit via modulating cellular redox signalling. Over 250 proteins, including receptors, ion channels and pumps, and signalling proteins are found in the caveolae. An increasing proportion of these are being recognized as redox regulated-proteins, that reside in the immediate vicinity of the two major cellular sources of ROS, nicotinamide adenine dinucleotide phosphate oxidase (Nox) and uncoupled endothelial nitric oxide synthase (eNOS). This review focuses on what is known about redox signalling within the caveolae, as well as endogenous protective mechanisms utilized by the cell, and new approaches to targeting dysregulated redox signalling in the caveolae as a therapeutic strategy in CVD. Copyright © 2017. Published by Elsevier Inc.

  9. Abscisic-acid-induced cellular apoptosis and differentiation in glioma via the retinoid acid signaling pathway.

    Science.gov (United States)

    Zhou, Nan; Yao, Yu; Ye, Hongxing; Zhu, Wei; Chen, Liang; Mao, Ying

    2016-04-15

    Retinoid acid (RA) plays critical roles in regulating differentiation and apoptosis in a variety of cancer cells. Abscisic acid (ABA) and RA are direct derivatives of carotenoids and share structural similarities. Here we proposed that ABA may also play a role in cellular differentiation and apoptosis by sharing a similar signaling pathway with RA that may be involved in glioma pathogenesis. We reported for the first time that the ABA levels were twofold higher in low-grade gliomas compared with high-grade gliomas. In glioma tissues, there was a positive correlation between the ABA levels and the transcription of cellular retinoic acid-binding protein 2 (CRABP2) and a negative correlation between the ABA levels and transcription of fatty acid-binding protein 5 (FABP5). ABA treatment induced a significant increase in the expression of CRABP2 and a decrease in the expression of peroxisome proliferator-activated receptor (PPAR) in glioblastoma cells. Remarkably, both cellular apoptosis and differentiation were increased in the glioblastoma cells after ABA treatment. ABA-induced cellular apoptosis and differentiation were significantly reduced by selectively silencing RAR-α, while RAR-α overexpression exaggerated the ABA-induced effects. These results suggest that ABA may play a role in the pathogenesis of glioma by promoting cellular apoptosis and differentiation through the RA signaling pathway. © 2015 UICC.

  10. Full-Duplex Communications in Large-Scale Cellular Networks

    KAUST Repository

    AlAmmouri, Ahmad

    2016-04-01

    In-band full-duplex (FD) communications have been optimistically promoted to improve the spectrum utilization and efficiency. However, the penetration of FD communications to the cellular networks domain is challenging due to the imposed uplink/downlink interference. This thesis presents a tractable framework, based on stochastic geometry, to study FD communications in multi-tier cellular networks. Particularly, we assess the FD communications effect on the network performance and quantify the associated gains. The study proves the vulnerability of the uplink to the downlink interference and shows that the improved FD rate gains harvested in the downlink (up to 97%) comes at the expense of a significant degradation in the uplink rate (up to 94%). Therefore, we propose a novel fine-grained duplexing scheme, denoted as α-duplex scheme, which allows a partial overlap between the uplink and the downlink frequency bands. We derive the required conditions to harvest rate gains from the α-duplex scheme and show its superiority to both the FD and half-duplex (HD) schemes. In particular, we show that the α-duplex scheme provides a simultaneous improvement of 28% for the downlink rate and 56% for the uplink rate. We also show that the amount of the overlap can be optimized based on the network design objective. Moreover, backward compatibility is an essential ingredient for the success of new technologies. In the context of in-band FD communication, FD base stations (BSs) should support HD users\\' equipment (UEs) without sacrificing the foreseen FD gains. The results show that FD-UEs are not necessarily required to harvest rate gains from FD-BSs. In particular, the results show that adding FD-UEs to FD-BSs offers a maximum of 5% rate gain over FD-BSs and HD-UEs case, which is a marginal gain compared to the burden required to implement FD transceivers at the UEs\\' side. To this end, we shed light on practical scenarios where HD-UEs operation with FD-BSs outperforms the

  11. Synaptic network activity induces neuronal differentiation of adult hippocampal precursor cells through BDNF signaling

    Directory of Open Access Journals (Sweden)

    Harish Babu

    2009-09-01

    Full Text Available Adult hippocampal neurogenesis is regulated by activity. But how do neural precursor cells in the hippocampus respond to surrounding network activity and translate increased neural activity into a developmental program? Here we show that long-term potential (LTP-like synaptic activity within a cellular network of mature hippocampal neurons promotes neuronal differentiation of newly generated cells. In co-cultures of precursor cells with primary hippocampal neurons, LTP-like synaptic plasticity induced by addition of glycine in Mg2+-free media for 5 min, produced synchronous network activity and subsequently increased synaptic strength between neurons. Furthermore, this synchronous network activity led to a significant increase in neuronal differentiation from the co-cultured neural precursor cells. When applied directly to precursor cells, glycine and Mg2+-free solution did not induce neuronal differentiation. Synaptic plasticity-induced neuronal differentiation of precursor cells was observed in the presence of GABAergic neurotransmission blockers but was dependent on NMDA-mediated Ca2+ influx. Most importantly, neuronal differentiation required the release of brain-derived neurotrophic factor (BDNF from the underlying substrate hippocampal neurons as well as TrkB receptor phosphorylation in precursor cells. This suggests that activity-dependent stem cell differentiation within the hippocampal network is mediated via synaptically evoked BDNF signaling.

  12. Integration of Neural Networks and Cellular Automata for Urban Planning

    Institute of Scientific and Technical Information of China (English)

    Anthony Gar-on Yeh; LI Xia

    2004-01-01

    This paper presents a new type of cellular automata (CA) model for the simulation of alternative land development using neural networks for urban planning. CA models can be regarded as a planning tool because they can generate alternative urban growth. Alternative development patterns can be formed by using different sets of parameter values in CA simulation. A critical issue is how to define parameter values for realistic and idealized simulation. This paper demonstrates that neural networks can simplify CA models but generate more plausible results. The simulation is based on a simple three-layer network with an output neuron to generate conversion probability. No transition rules are required for the simulation. Parameter values are automatically obtained from the training of network by using satellite remote sensing data. Original training data can be assessed and modified according to planning objectives. Alternative urban patterns can be easily formulated by using the modified training data sets rather than changing the model.

  13. RAINLINK: Retrieval algorithm for rainfall monitoring employing microwave links from a cellular communication network

    Science.gov (United States)

    Uijlenhoet, R.; Overeem, A.; Leijnse, H.; Rios Gaona, M. F.

    2017-12-01

    The basic principle of rainfall estimation using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated, which can be converted to average rainfall intensities over the length of a link. Microwave links from cellular communication networks have been proposed as a promising new rainfall measurement technique for one decade. They are particularly interesting for those countries where few surface rainfall observations are available. Yet to date no operational (real-time) link-based rainfall products are available. To advance the process towards operational application and upscaling of this technique, there is a need for freely available, user-friendly computer code for microwave link data processing and rainfall mapping. Such software is now available as R package "RAINLINK" on GitHub (https://github.com/overeem11/RAINLINK). It contains a working example to compute link-based 15-min rainfall maps for the entire surface area of The Netherlands for 40 hours from real microwave link data. This is a working example using actual data from an extensive network of commercial microwave links, for the first time, which will allow users to test their own algorithms and compare their results with ours. The package consists of modular functions, which facilitates running only part of the algorithm. The main processings steps are: 1) Preprocessing of link data (initial quality and consistency checks); 2) Wet-dry classification using link data; 3) Reference signal determination; 4) Removal of outliers ; 5) Correction of received signal powers; 6) Computation of mean path-averaged rainfall intensities; 7) Interpolation of rainfall intensities ; 8) Rainfall map visualisation. Some applications of RAINLINK will be shown based on microwave link data from a

  14. Information processing in network architecture of genome controlled signal transduction circuit. A proposed theoretical explanation.

    Science.gov (United States)

    Chakraborty, Chiranjib; Sarkar, Bimal Kumar; Patel, Pratiksha; Agoramoorthy, Govindasamy

    2012-01-01

    In this paper, Shannon information theory has been applied to elaborate cell signaling. It is proposed that in the cellular network architecture, four components viz. source (DNA), transmitter (mRNA), receiver (protein) and destination (another protein) are involved. The message transmits from source (DNA) to transmitter (mRNA) and then passes through a noisy channel reaching finally the receiver (protein). The protein synthesis process is here considered as the noisy channel. Ultimately, signal is transmitted from receiver to destination (another protein). The genome network architecture elements were compared with genetic alphabet L = {A, C, G, T} with a biophysical model based on the popular Shannon information theory. This study found the channel capacity as maximum for zero error (sigma = 0) and at this condition, transition matrix becomes a unit matrix with rank 4. The transition matrix will be erroneous and finally at sigma = 1 channel capacity will be localized maxima with a value of 0.415 due to the increased value at sigma. On the other hand, minima exists at sigma = 0.75, where all transition probabilities become 0.25 and uncertainty will be maximum resulting in channel capacity with the minima value of zero.

  15. Assuring SS7 dependability: A robustness characterization of signaling network elements

    Science.gov (United States)

    Karmarkar, Vikram V.

    1994-04-01

    Current and evolving telecommunication services will rely on signaling network performance and reliability properties to build competitive call and connection control mechanisms under increasing demands on flexibility without compromising on quality. The dimensions of signaling dependability most often evaluated are the Rate of Call Loss and End-to-End Route Unavailability. A third dimension of dependability that captures the concern about large or catastrophic failures can be termed Network Robustness. This paper is concerned with the dependability aspects of the evolving Signaling System No. 7 (SS7) networks and attempts to strike a balance between the probabilistic and deterministic measures that must be evaluated to accomplish a risk-trend assessment to drive architecture decisions. Starting with high-level network dependability objectives and field experience with SS7 in the U.S., potential areas of growing stringency in network element (NE) dependability are identified to improve against current measures of SS7 network quality, as per-call signaling interactions increase. A sensitivity analysis is presented to highlight the impact due to imperfect coverage of duplex network component or element failures (i.e., correlated failures), to assist in the setting of requirements on NE robustness. A benefit analysis, covering several dimensions of dependability, is used to generate the domain of solutions available to the network architect in terms of network and network element fault tolerance that may be specified to meet the desired signaling quality goals.

  16. Cooperative Handover Management in Dense Cellular Networks

    KAUST Repository

    Arshad, Rabe; Elsawy, Hesham; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2017-01-01

    Network densification has always been an important factor to cope with the ever increasing capacity demand. Deploying more base stations (BSs) improves the spatial frequency utilization, which increases the network capacity. However, such improvement comes at the expense of shrinking the BSs' footprints, which increases the handover (HO) rate and may diminish the foreseen capacity gains. In this paper, we propose a cooperative HO management scheme to mitigate the HO effect on throughput gains achieved via cellular network densification. The proposed HO scheme relies on skipping HO to the nearest BS at some instances along the user's trajectory while enabling cooperative BS service during HO execution at other instances. To this end, we develop a mathematical model, via stochastic geometry, to quantify the performance of the proposed HO scheme in terms of coverage probability and user throughput. The results show that the proposed cooperative HO scheme outperforms the always best connected based association at high mobility. Also, the value of BS cooperation along with handover skipping is quantified with respect to the HO skipping only that has recently appeared in the literature. Particularly, the proposed cooperative HO scheme shows throughput gains of 12% to 27% and 17% on average, when compared to the always best connected and HO skipping only schemes at user velocity ranging from 80 km/h to 160 Km/h, respectively.

  17. Cooperative Handover Management in Dense Cellular Networks

    KAUST Repository

    Arshad, Rabe

    2017-02-07

    Network densification has always been an important factor to cope with the ever increasing capacity demand. Deploying more base stations (BSs) improves the spatial frequency utilization, which increases the network capacity. However, such improvement comes at the expense of shrinking the BSs\\' footprints, which increases the handover (HO) rate and may diminish the foreseen capacity gains. In this paper, we propose a cooperative HO management scheme to mitigate the HO effect on throughput gains achieved via cellular network densification. The proposed HO scheme relies on skipping HO to the nearest BS at some instances along the user\\'s trajectory while enabling cooperative BS service during HO execution at other instances. To this end, we develop a mathematical model, via stochastic geometry, to quantify the performance of the proposed HO scheme in terms of coverage probability and user throughput. The results show that the proposed cooperative HO scheme outperforms the always best connected based association at high mobility. Also, the value of BS cooperation along with handover skipping is quantified with respect to the HO skipping only that has recently appeared in the literature. Particularly, the proposed cooperative HO scheme shows throughput gains of 12% to 27% and 17% on average, when compared to the always best connected and HO skipping only schemes at user velocity ranging from 80 km/h to 160 Km/h, respectively.

  18. On the distribution and mean of received power in stochastic cellular network

    OpenAIRE

    Cao, Fengming; Ganesh, Ayalvadi; Armour, Simon; Sooriyabandara, Mahesh

    2016-01-01

    This paper exploits the distribution and mean of received power for cellular network with stochastic network modeling to study the difference between the two cell association criteria, i.e. the strongest received power based cell association and the closest distance based cell association. Consequently we derive the analytical expression of the distribution and the mean of the nth strongest received power and the received power from the nth nearest base station and the derivations have been c...

  19. Global exponential stability of mixed discrete and distributively delayed cellular neural network

    International Nuclear Information System (INIS)

    Yao Hong-Xing; Zhou Jia-Yan

    2011-01-01

    This paper concernes analysis for the global exponential stability of a class of recurrent neural networks with mixed discrete and distributed delays. It first proves the existence and uniqueness of the balance point, then by employing the Lyapunov—Krasovskii functional and Young inequality, it gives the sufficient condition of global exponential stability of cellular neural network with mixed discrete and distributed delays, in addition, the example is provided to illustrate the applicability of the result. (general)

  20. A knowledge representation meta-model for rule-based modelling of signalling networks

    Directory of Open Access Journals (Sweden)

    Adrien Basso-Blandin

    2016-03-01

    Full Text Available The study of cellular signalling pathways and their deregulation in disease states, such as cancer, is a large and extremely complex task. Indeed, these systems involve many parts and processes but are studied piecewise and their literatures and data are consequently fragmented, distributed and sometimes—at least apparently—inconsistent. This makes it extremely difficult to build significant explanatory models with the result that effects in these systems that are brought about by many interacting factors are poorly understood. The rule-based approach to modelling has shown some promise for the representation of the highly combinatorial systems typically found in signalling where many of the proteins are composed of multiple binding domains, capable of simultaneous interactions, and/or peptide motifs controlled by post-translational modifications. However, the rule-based approach requires highly detailed information about the precise conditions for each and every interaction which is rarely available from any one single source. Rather, these conditions must be painstakingly inferred and curated, by hand, from information contained in many papers—each of which contains only part of the story. In this paper, we introduce a graph-based meta-model, attuned to the representation of cellular signalling networks, which aims to ease this massive cognitive burden on the rule-based curation process. This meta-model is a generalization of that used by Kappa and BNGL which allows for the flexible representation of knowledge at various levels of granularity. In particular, it allows us to deal with information which has either too little, or too much, detail with respect to the strict rule-based meta-model. Our approach provides a basis for the gradual aggregation of fragmented biological knowledge extracted from the literature into an instance of the meta-model from which we can define an automated translation into executable Kappa programs.

  1. Differential contribution of key metabolic substrates and cellular oxygen in HIF signalling

    Energy Technology Data Exchange (ETDEWEB)

    Zhdanov, Alexander V., E-mail: a.zhdanov@ucc.ie [School of Biochemistry and Cell Biology, University College Cork, Cavanagh Pharmacy Building, College Road, Cork (Ireland); Waters, Alicia H.C. [School of Biochemistry and Cell Biology, University College Cork, Cavanagh Pharmacy Building, College Road, Cork (Ireland); Golubeva, Anna V. [Alimentary Pharmabiotic Centre, University College Cork, Bioscience Institute, Western Road, Cork (Ireland); Papkovsky, Dmitri B. [School of Biochemistry and Cell Biology, University College Cork, Cavanagh Pharmacy Building, College Road, Cork (Ireland)

    2015-01-01

    Changes in availability and utilisation of O{sub 2} and metabolic substrates are common in ischemia and cancer. We examined effects of substrate deprivation on HIF signalling in PC12 cells exposed to different atmospheric O{sub 2}. Upon 2–4 h moderate hypoxia, HIF-α protein levels were dictated by the availability of glutamine and glucose, essential for deep cell deoxygenation and glycolytic ATP flux. Nuclear accumulation of HIF-1α dramatically decreased upon inhibition of glutaminolysis or glutamine deprivation. Elevation of HIF-2α levels was transcription-independent and associated with the activation of Akt and Erk1/2. Upon 2 h anoxia, HIF-2α levels strongly correlated with cellular ATP, produced exclusively via glycolysis. Without glucose, HIF signalling was suppressed, giving way to other regulators of cell adaptation to energy crisis, e.g. AMPK. Consequently, viability of cells deprived of O{sub 2} and glucose decreased upon inhibition of AMPK with dorsomorphin. The capacity of cells to accumulate HIF-2α decreased after 24 h glucose deprivation. This effect, associated with increased AMPKα phosphorylation, was sensitive to dorsomorphin. In chronically hypoxic cells, glutamine played no major role in HIF-2α accumulation, which became mainly glucose-dependent. Overall, the availability of O{sub 2} and metabolic substrates intricately regulates HIF signalling by affecting cell oxygenation, ATP levels and pathways involved in production of HIF-α. - Highlights: • Gln and Glc regulate HIF levels in hypoxic cells by maintaining low O{sub 2} and high ATP. • HIF-α levels under anoxia correlate with cellular ATP and critically depend on Glc. • Gln and Glc modulate activity of Akt, Erk and AMPK, regulating HIF production. • HIF signalling is differentially inhibited by prolonged Glc and Gln deprivation. • Unlike Glc, Gln plays no major role in HIF signalling in chronically hypoxic cells.

  2. Differential contribution of key metabolic substrates and cellular oxygen in HIF signalling

    International Nuclear Information System (INIS)

    Zhdanov, Alexander V.; Waters, Alicia H.C.; Golubeva, Anna V.; Papkovsky, Dmitri B.

    2015-01-01

    Changes in availability and utilisation of O 2 and metabolic substrates are common in ischemia and cancer. We examined effects of substrate deprivation on HIF signalling in PC12 cells exposed to different atmospheric O 2 . Upon 2–4 h moderate hypoxia, HIF-α protein levels were dictated by the availability of glutamine and glucose, essential for deep cell deoxygenation and glycolytic ATP flux. Nuclear accumulation of HIF-1α dramatically decreased upon inhibition of glutaminolysis or glutamine deprivation. Elevation of HIF-2α levels was transcription-independent and associated with the activation of Akt and Erk1/2. Upon 2 h anoxia, HIF-2α levels strongly correlated with cellular ATP, produced exclusively via glycolysis. Without glucose, HIF signalling was suppressed, giving way to other regulators of cell adaptation to energy crisis, e.g. AMPK. Consequently, viability of cells deprived of O 2 and glucose decreased upon inhibition of AMPK with dorsomorphin. The capacity of cells to accumulate HIF-2α decreased after 24 h glucose deprivation. This effect, associated with increased AMPKα phosphorylation, was sensitive to dorsomorphin. In chronically hypoxic cells, glutamine played no major role in HIF-2α accumulation, which became mainly glucose-dependent. Overall, the availability of O 2 and metabolic substrates intricately regulates HIF signalling by affecting cell oxygenation, ATP levels and pathways involved in production of HIF-α. - Highlights: • Gln and Glc regulate HIF levels in hypoxic cells by maintaining low O 2 and high ATP. • HIF-α levels under anoxia correlate with cellular ATP and critically depend on Glc. • Gln and Glc modulate activity of Akt, Erk and AMPK, regulating HIF production. • HIF signalling is differentially inhibited by prolonged Glc and Gln deprivation. • Unlike Glc, Gln plays no major role in HIF signalling in chronically hypoxic cells

  3. A dynamic genetic-hormonal regulatory network model explains multiple cellular behaviors of the root apical meristem of Arabidopsis thaliana.

    Science.gov (United States)

    García-Gómez, Mónica L; Azpeitia, Eugenio; Álvarez-Buylla, Elena R

    2017-04-01

    The study of the concerted action of hormones and transcription factors is fundamental to understand cell differentiation and pattern formation during organ development. The root apical meristem of Arabidopsis thaliana is a useful model to address this. It has a stem cell niche near its tip conformed of a quiescent organizer and stem or initial cells around it, then a proliferation domain followed by a transition domain, where cells diminish division rate before transiting to the elongation zone; here, cells grow anisotropically prior to their final differentiation towards the plant base. A minimal model of the gene regulatory network that underlies cell-fate specification and patterning at the root stem cell niche was proposed before. In this study, we update and couple such network with both the auxin and cytokinin hormone signaling pathways to address how they collectively give rise to attractors that correspond to the genetic and hormonal activity profiles that are characteristic of different cell types along A. thaliana root apical meristem. We used a Boolean model of the genetic-hormonal regulatory network to integrate known and predicted regulatory interactions into alternative models. Our analyses show that, after adding some putative missing interactions, the model includes the necessary and sufficient components and regulatory interactions to recover attractors characteristic of the root cell types, including the auxin and cytokinin activity profiles that correlate with different cellular behaviors along the root apical meristem. Furthermore, the model predicts the existence of activity configurations that could correspond to the transition domain. The model also provides a possible explanation for apparently paradoxical cellular behaviors in the root meristem. For example, how auxin may induce and at the same time inhibit WOX5 expression. According to the model proposed here the hormonal regulation of WOX5 might depend on the cell type. Our results

  4. A dynamic genetic-hormonal regulatory network model explains multiple cellular behaviors of the root apical meristem of Arabidopsis thaliana.

    Directory of Open Access Journals (Sweden)

    Mónica L García-Gómez

    2017-04-01

    Full Text Available The study of the concerted action of hormones and transcription factors is fundamental to understand cell differentiation and pattern formation during organ development. The root apical meristem of Arabidopsis thaliana is a useful model to address this. It has a stem cell niche near its tip conformed of a quiescent organizer and stem or initial cells around it, then a proliferation domain followed by a transition domain, where cells diminish division rate before transiting to the elongation zone; here, cells grow anisotropically prior to their final differentiation towards the plant base. A minimal model of the gene regulatory network that underlies cell-fate specification and patterning at the root stem cell niche was proposed before. In this study, we update and couple such network with both the auxin and cytokinin hormone signaling pathways to address how they collectively give rise to attractors that correspond to the genetic and hormonal activity profiles that are characteristic of different cell types along A. thaliana root apical meristem. We used a Boolean model of the genetic-hormonal regulatory network to integrate known and predicted regulatory interactions into alternative models. Our analyses show that, after adding some putative missing interactions, the model includes the necessary and sufficient components and regulatory interactions to recover attractors characteristic of the root cell types, including the auxin and cytokinin activity profiles that correlate with different cellular behaviors along the root apical meristem. Furthermore, the model predicts the existence of activity configurations that could correspond to the transition domain. The model also provides a possible explanation for apparently paradoxical cellular behaviors in the root meristem. For example, how auxin may induce and at the same time inhibit WOX5 expression. According to the model proposed here the hormonal regulation of WOX5 might depend on the cell

  5. Weak signal transmission in complex networks and its application in detecting connectivity.

    Science.gov (United States)

    Liang, Xiaoming; Liu, Zonghua; Li, Baowen

    2009-10-01

    We present a network model of coupled oscillators to study how a weak signal is transmitted in complex networks. Through both theoretical analysis and numerical simulations, we find that the response of other nodes to the weak signal decays exponentially with their topological distance to the signal source and the coupling strength between two neighboring nodes can be figured out by the responses. This finding can be conveniently used to detect the topology of unknown network, such as the degree distribution, clustering coefficient and community structure, etc., by repeatedly choosing different nodes as the signal source. Through four typical networks, i.e., the regular one dimensional, small world, random, and scale-free networks, we show that the features of network can be approximately given by investigating many fewer nodes than the network size, thus our approach to detect the topology of unknown network may be efficient in practical situations with large network size.

  6. Subsurface event detection and classification using Wireless Signal Networks.

    Science.gov (United States)

    Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T

    2012-11-05

    Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

  7. Resource Allocation for Multicell Device-to-Device Communications in Cellular Network: A Game Theoretic Approach

    Directory of Open Access Journals (Sweden)

    Jun Huang

    2015-08-01

    Full Text Available Device-to-Device (D2D communication has recently emerged as a promising technology to improve the capacity and coverage of cellular systems. To successfully implement D2D communications underlaying a cellular network, resource allocation for D2D links plays a critical role. While most of prior resource allocation mechanisms for D2D communications have focused on interference within a single-cell system, this paper investigates the resource allocation problem for a multicell cellular network in which a D2D link reuses available spectrum resources of multiple cells. A repeated game theoretic approach is proposed to address the problem. In this game, the base stations (BSs act as players that compete for resource supply of D2D, and the utility of each player is formulated as revenue collected from both cellular and D2D users using resources. Extensive simulations are conducted to verify the proposed approach and the results show that it can considerably enhance the system performance in terms of sum rate and sum rate gain.

  8. UTP-induced ATP release is a fine-tuned signalling pathway in osteocytes

    DEFF Research Database (Denmark)

    Kringelbach, Tina M.; Aslan, Derya; Novak, Ivana

    2014-01-01

    Osteocytes reside as a cellular network throughout the mineralised matrix of bone and are considered the primary mechanosensors of this tissue. They sense mechanical stimulation such as fluid flow and are able to regulate osteoblast and osteoclast functions on the bone surface. Previously, we fou...... signals may be propagated by P2 receptor activation and further ATP release in the osteocyte network and implicate purinergic signalling as a central signalling pathway in osteocyte mechanotransduction....

  9. Signalling network construction for modelling plant defence response.

    Directory of Open Access Journals (Sweden)

    Dragana Miljkovic

    Full Text Available Plant defence signalling response against various pathogens, including viruses, is a complex phenomenon. In resistant interaction a plant cell perceives the pathogen signal, transduces it within the cell and performs a reprogramming of the cell metabolism leading to the pathogen replication arrest. This work focuses on signalling pathways crucial for the plant defence response, i.e., the salicylic acid, jasmonic acid and ethylene signal transduction pathways, in the Arabidopsis thaliana model plant. The initial signalling network topology was constructed manually by defining the representation formalism, encoding the information from public databases and literature, and composing a pathway diagram. The manually constructed network structure consists of 175 components and 387 reactions. In order to complement the network topology with possibly missing relations, a new approach to automated information extraction from biological literature was developed. This approach, named Bio3graph, allows for automated extraction of biological relations from the literature, resulting in a set of (component1, reaction, component2 triplets and composing a graph structure which can be visualised, compared to the manually constructed topology and examined by the experts. Using a plant defence response vocabulary of components and reaction types, Bio3graph was applied to a set of 9,586 relevant full text articles, resulting in 137 newly detected reactions between the components. Finally, the manually constructed topology and the new reactions were merged to form a network structure consisting of 175 components and 524 reactions. The resulting pathway diagram of plant defence signalling represents a valuable source for further computational modelling and interpretation of omics data. The developed Bio3graph approach, implemented as an executable language processing and graph visualisation workflow, is publically available at http://ropot.ijs.si/bio3graph/and can be

  10. The influence of cold temperature on cellular excitability of hippocampal networks.

    Science.gov (United States)

    de la Peña, Elvira; Mälkiä, Annika; Vara, Hugo; Caires, Rebeca; Ballesta, Juan J; Belmonte, Carlos; Viana, Felix

    2012-01-01

    The hippocampus plays an important role in short term memory, learning and spatial navigation. A characteristic feature of the hippocampal region is its expression of different electrical population rhythms and activities during different brain states. Physiological fluctuations in brain temperature affect the activity patterns in hippocampus, but the underlying cellular mechanisms are poorly understood. In this work, we investigated the thermal modulation of hippocampal activity at the cellular network level. Primary cell cultures of mouse E17 hippocampus displayed robust network activation upon light cooling of the extracellular solution from baseline physiological temperatures. The activity generated was dependent on action potential firing and excitatory glutamatergic synaptic transmission. Involvement of thermosensitive channels from the transient receptor potential (TRP) family in network activation by temperature changes was ruled out, whereas pharmacological and immunochemical experiments strongly pointed towards the involvement of temperature-sensitive two-pore-domain potassium channels (K(2P)), TREK/TRAAK family. In hippocampal slices we could show an increase in evoked and spontaneous synaptic activity produced by mild cooling in the physiological range that was prevented by chloroform, a K(2P) channel opener. We propose that cold-induced closure of background TREK/TRAAK family channels increases the excitability of some hippocampal neurons, acting as a temperature-sensitive gate of network activation. Our findings in the hippocampus open the possibility that small temperature variations in the brain in vivo, associated with metabolism or blood flow oscillations, act as a switch mechanism of neuronal activity and determination of firing patterns through regulation of thermosensitive background potassium channel activity.

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

    Science.gov (United States)

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

    2017-01-01

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

  12. Cellular Architecture Regulates Collective Calcium Signaling and Cell Contractility.

    Directory of Open Access Journals (Sweden)

    Jian Sun

    2016-05-01

    Full Text Available A key feature of multicellular systems is the ability of cells to function collectively in response to external stimuli. However, the mechanisms of intercellular cell signaling and their functional implications in diverse vascular structures are poorly understood. Using a combination of computational modeling and plasma lithography micropatterning, we investigate the roles of structural arrangement of endothelial cells in collective calcium signaling and cell contractility. Under histamine stimulation, endothelial cells in self-assembled and microengineered networks, but not individual cells and monolayers, exhibit calcium oscillations. Micropatterning, pharmacological inhibition, and computational modeling reveal that the calcium oscillation depends on the number of neighboring cells coupled via gap junctional intercellular communication, providing a mechanistic basis of the architecture-dependent calcium signaling. Furthermore, the calcium oscillation attenuates the histamine-induced cytoskeletal reorganization and cell contraction, resulting in differential cell responses in an architecture-dependent manner. Taken together, our results suggest that endothelial cells can sense and respond to chemical stimuli according to the vascular architecture via collective calcium signaling.

  13. Application of neural networks and cellular automata to calorimetric problems

    International Nuclear Information System (INIS)

    Brenton, V.; Fonvieille, H.; Guicheney, C.; Jousset, J.; Roblin, Y.; Tamin, F.; Grenier, P.

    1994-09-01

    Computing techniques based on parallel processing have been used to treat the information from the electromagnetic calorimeters in SLAC experiments E142/E143. Cluster finding and separation of overlapping showers are performed by a cellular automaton, pion and electron identification is done by using a multilayered neural network. Both applications are presented and their resulting performances are shown to be improved compared to more standard approaches. (author)

  14. Global exponential stability of impulsive fuzzy cellular neural networks with mixed delays and reaction-diffusion terms

    International Nuclear Information System (INIS)

    Wang Xiaohu; Xu Daoyi

    2009-01-01

    In this paper, the global exponential stability of impulsive fuzzy cellular neural networks with mixed delays and reaction-diffusion terms is considered. By establishing an integro-differential inequality with impulsive initial condition and using the properties of M-cone and eigenspace of the spectral radius of nonnegative matrices, several new sufficient conditions are obtained to ensure the global exponential stability of the equilibrium point for fuzzy cellular neural networks with delays and reaction-diffusion terms. These results extend and improve the earlier publications. Two examples are given to illustrate the efficiency of the obtained results.

  15. Performance of Overlaid MIMO Cellular Networks with TAS/MRC under Hybrid-Access Small Cells and Poisson Field Interference

    KAUST Repository

    AbdelNabi, Amr A.

    2018-02-12

    This paper presents new approaches to characterize the achieved performance of hybrid control-access small cells in the context of two-tier multi-input multi-output (MIMO) cellular networks with random interference distributions. The hybrid scheme at small cells (such as femtocells) allows for sharing radio resources between the two network tiers according to the densities of small cells and their associated users, as well as the observed interference power levels in the two network tiers. The analysis considers MIMO transceivers at all nodes, for which antenna arrays can be utilized to implement transmit antenna selection (TAS) and receive maximal ratio combining (MRC) under MIMO point-to-point channels. Moreover, it tar-gets network-level models of interference sources inside each tier and between the two tiers, which are assumed to follow Poisson field processes. To fully capture the occasions for Poisson field distribution on MIMO spatial domain. Two practical scenarios of interference sources are addressed including highly-correlated or uncorrelated transmit antenna arrays of the serving macrocell base station. The analysis presents new analytical approaches that can characterize the downlink outage probability performance in any tier. Furthermore, the outage performance in high signal-to-noise (SNR) regime is also obtained, which can be useful to deduce diversity and/or coding gains.

  16. Performance of Overlaid MIMO Cellular Networks with TAS/MRC under Hybrid-Access Small Cells and Poisson Field Interference

    KAUST Repository

    AbdelNabi, Amr A.; Al-Qahtani, Fawaz S.; Radaydeh, Redha Mahmoud Mesleh; Shaqfeh, Mohammad; Manna, Raed F.

    2018-01-01

    This paper presents new approaches to characterize the achieved performance of hybrid control-access small cells in the context of two-tier multi-input multi-output (MIMO) cellular networks with random interference distributions. The hybrid scheme at small cells (such as femtocells) allows for sharing radio resources between the two network tiers according to the densities of small cells and their associated users, as well as the observed interference power levels in the two network tiers. The analysis considers MIMO transceivers at all nodes, for which antenna arrays can be utilized to implement transmit antenna selection (TAS) and receive maximal ratio combining (MRC) under MIMO point-to-point channels. Moreover, it tar-gets network-level models of interference sources inside each tier and between the two tiers, which are assumed to follow Poisson field processes. To fully capture the occasions for Poisson field distribution on MIMO spatial domain. Two practical scenarios of interference sources are addressed including highly-correlated or uncorrelated transmit antenna arrays of the serving macrocell base station. The analysis presents new analytical approaches that can characterize the downlink outage probability performance in any tier. Furthermore, the outage performance in high signal-to-noise (SNR) regime is also obtained, which can be useful to deduce diversity and/or coding gains.

  17. Nonlinear signaling on biological networks: The role of stochasticity and spectral clustering

    Science.gov (United States)

    Hernandez-Hernandez, Gonzalo; Myers, Jesse; Alvarez-Lacalle, Enrique; Shiferaw, Yohannes

    2017-03-01

    Signal transduction within biological cells is governed by networks of interacting proteins. Communication between these proteins is mediated by signaling molecules which bind to receptors and induce stochastic transitions between different conformational states. Signaling is typically a cooperative process which requires the occurrence of multiple binding events so that reaction rates have a nonlinear dependence on the amount of signaling molecule. It is this nonlinearity that endows biological signaling networks with robust switchlike properties which are critical to their biological function. In this study we investigate how the properties of these signaling systems depend on the network architecture. Our main result is that these nonlinear networks exhibit bistability where the network activity can switch between states that correspond to a low and high activity level. We show that this bistable regime emerges at a critical coupling strength that is determined by the spectral structure of the network. In particular, the set of nodes that correspond to large components of the leading eigenvector of the adjacency matrix determines the onset of bistability. Above this transition the eigenvectors of the adjacency matrix determine a hierarchy of clusters, defined by its spectral properties, which are activated sequentially with increasing network activity. We argue further that the onset of bistability occurs either continuously or discontinuously depending upon whether the leading eigenvector is localized or delocalized. Finally, we show that at low network coupling stochastic transitions to the active branch are also driven by the set of nodes that contribute more strongly to the leading eigenvector. However, at high coupling, transitions are insensitive to network structure since the network can be activated by stochastic transitions of a few nodes. Thus this work identifies important features of biological signaling networks that may underlie their biological

  18. Low-complexity co-tier interference reduction scheme in open-access overlaid cellular networks

    KAUST Repository

    Radaydeh, Redha Mahmoud Mesleh; Alouini, Mohamed-Slim

    2011-01-01

    This paper addresses the effect of co-tier interference on the performance of multiuser overlaid cellular networks that share the same available resources. It assumed that each macrocell contains a number of self-configurable and randomly located

  19. A multi-scale convolutional neural network for phenotyping high-content cellular images.

    Science.gov (United States)

    Godinez, William J; Hossain, Imtiaz; Lazic, Stanley E; Davies, John W; Zhang, Xian

    2017-07-01

    Identifying phenotypes based on high-content cellular images is challenging. Conventional image analysis pipelines for phenotype identification comprise multiple independent steps, with each step requiring method customization and adjustment of multiple parameters. Here, we present an approach based on a multi-scale convolutional neural network (M-CNN) that classifies, in a single cohesive step, cellular images into phenotypes by using directly and solely the images' pixel intensity values. The only parameters in the approach are the weights of the neural network, which are automatically optimized based on training images. The approach requires no a priori knowledge or manual customization, and is applicable to single- or multi-channel images displaying single or multiple cells. We evaluated the classification performance of the approach on eight diverse benchmark datasets. The approach yielded overall a higher classification accuracy compared with state-of-the-art results, including those of other deep CNN architectures. In addition to using the network to simply obtain a yes-or-no prediction for a given phenotype, we use the probability outputs calculated by the network to quantitatively describe the phenotypes. This study shows that these probability values correlate with chemical treatment concentrations. This finding validates further our approach and enables chemical treatment potency estimation via CNNs. The network specifications and solver definitions are provided in Supplementary Software 1. william_jose.godinez_navarro@novartis.com or xian-1.zhang@novartis.com. 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

  20. Subsurface Event Detection and Classification Using Wireless Signal Networks

    Directory of Open Access Journals (Sweden)

    Muhannad T. Suleiman

    2012-11-01

    Full Text Available Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs. The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

  1. Hierarchical feedback modules and reaction hubs in cell signaling networks.

    Science.gov (United States)

    Xu, Jianfeng; Lan, Yueheng

    2015-01-01

    Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.

  2. Hierarchical feedback modules and reaction hubs in cell signaling networks.

    Directory of Open Access Journals (Sweden)

    Jianfeng Xu

    Full Text Available Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.

  3. Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

    Science.gov (United States)

    Xu, Jianfeng; Lan, Yueheng

    2015-01-01

    Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

  4. Chaos Control and Synchronization of Cellular Neural Network with Delays Based on OPNCL Control

    International Nuclear Information System (INIS)

    Qian, Tang; Xing-Yuan, Wang

    2010-01-01

    The problem of chaos control and complete synchronization of cellular neural network with delays is studied. Based on the open plus nonlinear closed loop (OPNCL) method, the control scheme and synchronization scheme are designed. Both the schemes can achieve the chaos control and complete synchronization of chaotic neural network respectively, and their validity is further verified by numerical simulation experiments. (general)

  5. Spatio-temporal analysis of brain electrical activity in epilepsy based on cellular nonlinear networks

    Science.gov (United States)

    Gollas, Frank; Tetzlaff, Ronald

    2009-05-01

    Epilepsy is the most common chronic disorder of the nervous system. Generally, epileptic seizures appear without foregoing sign or warning. The problem of detecting a possible pre-seizure state in epilepsy from EEG signals has been addressed by many authors over the past decades. Different approaches of time series analysis of brain electrical activity already are providing valuable insights into the underlying complex dynamics. But the main goal the identification of an impending epileptic seizure with a sufficient specificity and reliability, has not been achieved up to now. An algorithm for a reliable, automated prediction of epileptic seizures would enable the realization of implantable seizure warning devices, which could provide valuable information to the patient and time/event specific drug delivery or possibly a direct electrical nerve stimulation. Cellular Nonlinear Networks (CNN) are promising candidates for future seizure warning devices. CNN are characterized by local couplings of comparatively simple dynamical systems. With this property these networks are well suited to be realized as highly parallel, analog computer chips. Today available CNN hardware realizations exhibit a processing speed in the range of TeraOps combined with low power consumption. In this contribution new algorithms based on the spatio-temporal dynamics of CNN are considered in order to analyze intracranial EEG signals and thus taking into account mutual dependencies between neighboring regions of the brain. In an identification procedure Reaction-Diffusion CNN (RD-CNN) are determined for short segments of brain electrical activity, by means of a supervised parameter optimization. RD-CNN are deduced from Reaction-Diffusion Systems, which usually are applied to investigate complex phenomena like nonlinear wave propagation or pattern formation. The Local Activity Theory provides a necessary condition for emergent behavior in RD-CNN. In comparison linear spatio

  6. Cognitive radio networks efficient resource allocation in cooperative sensing, cellular communications, high-speed vehicles, and smart grid

    CERN Document Server

    Jiang, Tao; Cao, Yang

    2015-01-01

    PrefaceAcknowledgmentsAbout the AuthorsIntroductionCognitive Radio-Based NetworksOpportunistic Spectrum Access NetworksCognitive Radio Networks with Cooperative SensingCognitive Radio Networks for Cellular CommunicationsCognitive Radio Networks for High-Speed VehiclesCognitive Radio Networks for a Smart GridContent and OrganizationTransmission Slot Allocation in an Opportunistic Spectrum Access NetworkSingle-User Single-Channel System ModelProbabilistic Slot Allocation SchemeOptimal Probabilistic Slot AllocationBaseline PerformanceExponential DistributionHyper-Erlang DistributionPerformance An

  7. Cellular Signal Mechanisms of Reward-Related Plasticity in the Hippocampus

    Directory of Open Access Journals (Sweden)

    Masako Isokawa

    2012-01-01

    Full Text Available The hippocampus has the extraordinary capacity to process and store information. Consequently, there is an intense interest in the mechanisms that underline learning and memory. Synaptic plasticity has been hypothesized to be the neuronal substrate for learning. Ca2+ and Ca2+-activated kinases control cellular processes of most forms of hippocampal synapse plasticity. In this paper, I aim to integrate our current understanding of Ca2+-mediated synaptic plasticity and metaplasticity in motivational and reward-related learning in the hippocampus. I will introduce two representative neuromodulators that are widely studied in reward-related learning (e.g., ghrelin and endocannabinoids and show how they might contribute to hippocampal neuron activities and Ca2+-mediated signaling processes in synaptic plasticity. Additionally, I will discuss functional significance of these two systems and their signaling pathways for its relevance to maladaptive reward learning leading to addiction.

  8. Load-induced modulation of signal transduction networks.

    Science.gov (United States)

    Jiang, Peng; Ventura, Alejandra C; Sontag, Eduardo D; Merajver, Sofia D; Ninfa, Alexander J; Del Vecchio, Domitilla

    2011-10-11

    Biological signal transduction networks are commonly viewed as circuits that pass along information--in the process amplifying signals, enhancing sensitivity, or performing other signal-processing tasks--to transcriptional and other components. Here, we report on a "reverse-causality" phenomenon, which we call load-induced modulation. Through a combination of analytical and experimental tools, we discovered that signaling was modulated, in a surprising way, by downstream targets that receive the signal and, in doing so, apply what in physics is called a load. Specifically, we found that non-intuitive changes in response dynamics occurred for a covalent modification cycle when load was present. Loading altered the response time of a system, depending on whether the activity of one of the enzymes was maximal and the other was operating at its minimal rate or whether both enzymes were operating at submaximal rates. These two conditions, which we call "limit regime" and "intermediate regime," were associated with increased or decreased response times, respectively. The bandwidth, the range of frequency in which the system can process information, decreased in the presence of load, suggesting that downstream targets participate in establishing a balance between noise-filtering capabilities and a circuit's ability to process high-frequency stimulation. Nodes in a signaling network are not independent relay devices, but rather are modulated by their downstream targets.

  9. Signaling mechanisms underlying the robustness and tunability of the plant immune network

    Science.gov (United States)

    Kim, Yungil; Tsuda, Kenichi; Igarashi, Daisuke; Hillmer, Rachel A.; Sakakibara, Hitoshi; Myers, Chad L.; Katagiri, Fumiaki

    2014-01-01

    Summary How does robust and tunable behavior emerge in a complex biological network? We sought to understand this for the signaling network controlling pattern-triggered immunity (PTI) in Arabidopsis. A dynamic network model containing four major signaling sectors, the jasmonate, ethylene, PAD4, and salicylate sectors, which together explain up to 80% of the PTI level, was built using data for dynamic sector activities and PTI levels under exhaustive combinatorial sector perturbations. Our regularized multiple regression model had a high level of predictive power and captured known and unexpected signal flows in the network. The sole inhibitory sector in the model, the ethylene sector, was central to the network robustness via its inhibition of the jasmonate sector. The model's multiple input sites linked specific signal input patterns varying in strength and timing to different network response patterns, indicating a mechanism enabling tunability. PMID:24439900

  10. Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

    Science.gov (United States)

    Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

    2016-11-01

    Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

  11. Electrocardiogram (ECG Signal Modeling and Noise Reduction Using Hopfield Neural Networks

    Directory of Open Access Journals (Sweden)

    F. Bagheri

    2013-02-01

    Full Text Available The Electrocardiogram (ECG signal is one of the diagnosing approaches to detect heart disease. In this study the Hopfield Neural Network (HNN is applied and proposed for ECG signal modeling and noise reduction. The Hopfield Neural Network (HNN is a recurrent neural network that stores the information in a dynamic stable pattern. This algorithm retrieves a pattern stored in memory in response to the presentation of an incomplete or noisy version of that pattern. Computer simulation results show that this method can successfully model the ECG signal and remove high-frequency noise.

  12. Discrete dynamic modeling of T cell survival signaling networks

    Science.gov (United States)

    Zhang, Ranran

    2009-03-01

    Biochemistry-based frameworks are often not applicable for the modeling of heterogeneous regulatory systems that are sparsely documented in terms of quantitative information. As an alternative, qualitative models assuming a small set of discrete states are gaining acceptance. This talk will present a discrete dynamic model of the signaling network responsible for the survival and long-term competence of cytotoxic T cells in the blood cancer T-LGL leukemia. We integrated the signaling pathways involved in normal T cell activation and the known deregulations of survival signaling in leukemic T-LGL, and formulated the regulation of each network element as a Boolean (logic) rule. Our model suggests that the persistence of two signals is sufficient to reproduce all known deregulations in leukemic T-LGL. It also indicates the nodes whose inactivity is necessary and sufficient for the reversal of the T-LGL state. We have experimentally validated several model predictions, including: (i) Inhibiting PDGF signaling induces apoptosis in leukemic T-LGL. (ii) Sphingosine kinase 1 and NFκB are essential for the long-term survival of T cells in T-LGL leukemia. (iii) T box expressed in T cells (T-bet) is constitutively activated in the T-LGL state. The model has identified potential therapeutic targets for T-LGL leukemia and can be used for generating long-term competent CTL necessary for tumor and cancer vaccine development. The success of this model, and of other discrete dynamic models, suggests that the organization of signaling networks has an determining role in their dynamics. Reference: R. Zhang, M. V. Shah, J. Yang, S. B. Nyland, X. Liu, J. K. Yun, R. Albert, T. P. Loughran, Jr., Network Model of Survival Signaling in LGL Leukemia, PNAS 105, 16308-16313 (2008).

  13. A central integrator of transcription networks in plant stress and energy signalling.

    Science.gov (United States)

    Baena-González, Elena; Rolland, Filip; Thevelein, Johan M; Sheen, Jen

    2007-08-23

    Photosynthetic plants are the principal solar energy converter sustaining life on Earth. Despite its fundamental importance, little is known about how plants sense and adapt to darkness in the daily light-dark cycle, or how they adapt to unpredictable environmental stresses that compromise photosynthesis and respiration and deplete energy supplies. Current models emphasize diverse stress perception and signalling mechanisms. Using a combination of cellular and systems screens, we show here that the evolutionarily conserved Arabidopsis thaliana protein kinases, KIN10 and KIN11 (also known as AKIN10/At3g01090 and AKIN11/At3g29160, respectively), control convergent reprogramming of transcription in response to seemingly unrelated darkness, sugar and stress conditions. Sensing and signalling deprivation of sugar and energy, KIN10 targets a remarkably broad array of genes that orchestrate transcription networks, promote catabolism and suppress anabolism. Specific bZIP transcription factors partially mediate primary KIN10 signalling. Transgenic KIN10 overexpression confers enhanced starvation tolerance and lifespan extension, and alters architecture and developmental transitions. Significantly, double kin10 kin11 deficiency abrogates the transcriptional switch in darkness and stress signalling, and impairs starch mobilization at night and growth. These studies uncover surprisingly pivotal roles of KIN10/11 in linking stress, sugar and developmental signals to globally regulate plant metabolism, energy balance, growth and survival. In contrast to the prevailing view that sucrose activates plant SnRK1s (Snf1-related protein kinases), our functional analyses of Arabidopsis KIN10/11 provide compelling evidence that SnRK1s are inactivated by sugars and share central roles with the orthologous yeast Snf1 and mammalian AMPK in energy signalling.

  14. Signal processing for molecular and cellular biological physics: an emerging field.

    Science.gov (United States)

    Little, Max A; Jones, Nick S

    2013-02-13

    Recent advances in our ability to watch the molecular and cellular processes of life in action--such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer--raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied.

  15. Energy Management Optimization for Cellular Networks under Renewable Energy Generation Uncertainty

    KAUST Repository

    Rached, Nadhir B.

    2017-03-28

    The integration of renewable energy (RE) as an alternative power source for cellular networks has been deeply investigated in literature. However, RE generation is often assumed to be deterministic; an impractical assumption for realistic scenarios. In this paper, an efficient energy procurement strategy for cellular networks powered simultaneously by the smart grid (SG) and locally deployed RE sources characterized by uncertain processes is proposed. For a one-day operation cycle, the mobile operator aims to reduce its total energy cost by optimizing the amounts of energy to be procured from the local RE sources and SG at each time period. Additionally, it aims to determine the amount of extra generated RE to be sold back to SG. A chance constrained optimization is first proposed to deal with the RE generation uncertainty. Then, two convex approximation approaches: Chernoff and Chebyshev methods, characterized by different levels of knowledge about the RE generation, are developed to determine the energy procurement strategy for different risk levels. In addition, their performances are analyzed for various daily scenarios through selected simulation results. It is shown that the higher complex Chernoff method outperforms the Chebyshev one for different risk levels set by the operator.

  16. Energy Management Optimization for Cellular Networks under Renewable Energy Generation Uncertainty

    KAUST Repository

    Rached, Nadhir B.; Ghazzai, Hakim; Kadri, Abdullah; Alouini, Mohamed-Slim

    2017-01-01

    The integration of renewable energy (RE) as an alternative power source for cellular networks has been deeply investigated in literature. However, RE generation is often assumed to be deterministic; an impractical assumption for realistic scenarios. In this paper, an efficient energy procurement strategy for cellular networks powered simultaneously by the smart grid (SG) and locally deployed RE sources characterized by uncertain processes is proposed. For a one-day operation cycle, the mobile operator aims to reduce its total energy cost by optimizing the amounts of energy to be procured from the local RE sources and SG at each time period. Additionally, it aims to determine the amount of extra generated RE to be sold back to SG. A chance constrained optimization is first proposed to deal with the RE generation uncertainty. Then, two convex approximation approaches: Chernoff and Chebyshev methods, characterized by different levels of knowledge about the RE generation, are developed to determine the energy procurement strategy for different risk levels. In addition, their performances are analyzed for various daily scenarios through selected simulation results. It is shown that the higher complex Chernoff method outperforms the Chebyshev one for different risk levels set by the operator.

  17. One-way hash function based on hyper-chaotic cellular neural network

    International Nuclear Information System (INIS)

    Yang Qunting; Gao Tiegang

    2008-01-01

    The design of an efficient one-way hash function with good performance is a hot spot in modern cryptography researches. In this paper, a hash function construction method based on cell neural network with hyper-chaos characteristics is proposed. First, the chaos sequence is gotten by iterating cellular neural network with Runge–Kutta algorithm, and then the chaos sequence is iterated with the message. The hash code is obtained through the corresponding transform of the latter chaos sequence. Simulation and analysis demonstrate that the new method has the merit of convenience, high sensitivity to initial values, good hash performance, especially the strong stability. (general)

  18. Cellular chromophores and signaling in low level light therapy

    Science.gov (United States)

    Hamblin, Michael R.; Demidova-Rice, Tatiana N.

    2007-02-01

    particular, signaling cascades are initiated via cyclic adenosine monophosphate (cAMP) and nuclear factor kappa B (NF-κB). These signal transduction pathways in turn lead to increased cell proliferation and migration (particularly by fibroblasts), modulation in levels of cytokines, growth factors and inflammatory mediators, and increases in anti-apoptotic proteins. The results of these biochemical and cellular changes in animals and patients include such benefits as increased healing in chronic wounds, improvements in sports injuries and carpal tunnel syndrome, pain reduction in arthritis and neuropathies, and amelioration of damage after heart attacks, stroke, nerve injury and retinal toxicity.

  19. Global exponential stability of cellular neural networks with mixed delays and impulses

    International Nuclear Information System (INIS)

    Xiong Wanmin; Zhou Qiyuan; Xiao Bing; Yu Yuehua

    2007-01-01

    In this paper cellular neural networks with mixed delays and impulses are considered. Sufficient conditions for the existence and global exponential stability of a unique equilibrium point are established by using the fixed point theorem and differential inequality technique. The results of this paper are new and they complement previously known results

  20. Almost periodic cellular neural networks with neutral-type proportional delays

    Science.gov (United States)

    Xiao, Songlin

    2018-03-01

    This paper presents a new result on the existence, uniqueness and generalised exponential stability of almost periodic solutions for cellular neural networks with neutral-type proportional delays and D operator. Based on some novel differential inequality techniques, a testable condition is derived to ensure that all the state trajectories of the system converge to an almost periodic solution with a positive exponential convergence rate. The effectiveness of the obtained result is illustrated by a numerical example.

  1. Application of neural networks and cellular automata to calorimetric problems

    Energy Technology Data Exchange (ETDEWEB)

    Brenton, V; Fonvieille, H; Guicheney, C; Jousset, J; Roblin, Y; Tamin, F; Grenier, P

    1994-09-01

    Computing techniques based on parallel processing have been used to treat the information from the electromagnetic calorimeters in SLAC experiments E142/E143. Cluster finding and separation of overlapping showers are performed by a cellular automaton, pion and electron identification is done by using a multilayered neural network. Both applications are presented and their resulting performances are shown to be improved compared to more standard approaches. (author). 9 refs.; Submitted to Nuclear Instruments and Methods (NL).

  2. Cellular communications a comprehensive and practical guide

    CERN Document Server

    Tripathi, Nishith

    2014-01-01

    Even as newer cellular technologies and standards emerge, many of the fundamental principles and the components of the cellular network remain the same. Presenting a simple yet comprehensive view of cellular communications technologies, Cellular Communications provides an end-to-end perspective of cellular operations, ranging from physical layer details to call set-up and from the radio network to the core network. This self-contained source forpractitioners and students represents a comprehensive survey of the fundamentals of cellular communications and the landscape of commercially deployed

  3. Network analysis of oyster transcriptome revealed a cascade of cellular responses during recovery after heat shock.

    Directory of Open Access Journals (Sweden)

    Lingling Zhang

    Full Text Available Oysters, as a major group of marine bivalves, can tolerate a wide range of natural and anthropogenic stressors including heat stress. Recent studies have shown that oysters pretreated with heat shock can result in induced heat tolerance. A systematic study of cellular recovery from heat shock may provide insights into the mechanism of acquired thermal tolerance. In this study, we performed the first network analysis of oyster transcriptome by reanalyzing microarray data from a previous study. Network analysis revealed a cascade of cellular responses during oyster recovery after heat shock and identified responsive gene modules and key genes. Our study demonstrates the power of network analysis in a non-model organism with poor gene annotations, which can lead to new discoveries that go beyond the focus on individual genes.

  4. Performance Analysis of Dual-Polarized Massive MIMO System with Human-Care IoT Devices for Cellular Networks

    Directory of Open Access Journals (Sweden)

    Jun-Ki Hong

    2018-01-01

    Full Text Available The performance analysis of the dual-polarized massive multiple-input multiple-output (MIMO system with Internet of things (IoT devices is studied when outdoor human-care IoT devices are connected to a cellular network via a dual-polarized massive MIMO system. The research background of the performance analysis of dual-polarized massive MIMO system with IoT devices is that recently the data usage of outdoor human-care IoT devices has increased. Therefore, the outdoor human-care IoT devices are necessary to connect with 5G cellular networks which can expect 1000 times higher performance compared with 4G cellular networks. Moreover, in order to guarantee the safety of the patient for emergency cases, a human-care Iot device must be connected to cellular networks which offer more stable communication for outdoors compared to short-range communication technologies such as Wi-Fi, Zigbee, and Bluetooth. To analyze the performance of the dual-polarized massive MIMO system for human-care IoT devices, a dual-polarized MIMO spatial channel model (SCM is proposed which considers depolarization effect between the dual-polarized transmit-antennas and the receive-antennas. The simulation results show that the performance of the dual-polarized massive MIMO system is improved about 16% to 92% for 20 to 150 IoT devices compared to conventional single-polarized massive MIMO system for identical size of the transmit array.

  5. An integrated approach to elucidate the intra-viral and viral-cellular protein interaction networks of a gamma-herpesvirus.

    Directory of Open Access Journals (Sweden)

    Shaoying Lee

    2011-10-01

    Full Text Available Genome-wide yeast two-hybrid (Y2H screens were conducted to elucidate the molecular functions of open reading frames (ORFs encoded by murine γ-herpesvirus 68 (MHV-68. A library of 84 MHV-68 genes and gene fragments was generated in a Gateway entry plasmid and transferred to Y2H vectors. All possible pair-wise interactions between viral proteins were tested in the Y2H assay, resulting in the identification of 23 intra-viral protein-protein interactions (PPIs. Seventy percent of the interactions between viral proteins were confirmed by co-immunoprecipitation experiments. To systematically investigate virus-cellular protein interactions, the MHV-68 Y2H constructs were screened against a cellular cDNA library, yielding 243 viral-cellular PPIs involving 197 distinct cellar proteins. Network analyses indicated that cellular proteins targeted by MHV-68 had more partners in the cellular PPI network and were located closer to each other than expected by chance. Taking advantage of this observation, we scored the cellular proteins based on their network distances from other MHV-68-interacting proteins and segregated them into high (Y2H-HP and low priority/not-scored (Y2H-LP/NS groups. Significantly more genes from Y2H-HP altered MHV-68 replication when their expression was inhibited with siRNAs (53% of genes from Y2H-HP, 21% of genes from Y2H-LP/NS, and 16% of genes randomly chosen from the human PPI network; p<0.05. Enriched Gene Ontology (GO terms in the Y2H-HP group included regulation of apoptosis, protein kinase cascade, post-translational protein modification, transcription from RNA polymerase II promoter, and IκB kinase/NFκB cascade. Functional validation assays indicated that PCBP1, which interacted with MHV-68 ORF34, may be involved in regulating late virus gene expression in a manner consistent with the effects of its viral interacting partner. Our study integrated Y2H screening with multiple functional validation approaches to create

  6. Signal-BNF: A Bayesian Network Fusing Approach to Predict Signal Peptides

    Directory of Open Access Journals (Sweden)

    Zhi Zheng

    2012-01-01

    Full Text Available A signal peptide is a short peptide chain that directs the transport of a protein and has become the crucial vehicle in finding new drugs or reprogramming cells for gene therapy. As the avalanche of new protein sequences generated in the postgenomic era, the challenge of identifying new signal sequences has become even more urgent and critical in biomedical engineering. In this paper, we propose a novel predictor called Signal-BNF to predict the N-terminal signal peptide as well as its cleavage site based on Bayesian reasoning network. Signal-BNF is formed by fusing the results of different Bayesian classifiers which used different feature datasets as its input through weighted voting system. Experiment results show that Signal-BNF is superior to the popular online predictors such as Signal-3L and PrediSi. Signal-BNF is featured by high prediction accuracy that may serve as a useful tool for further investigating many unclear details regarding the molecular mechanism of the zip code protein-sorting system in cells.

  7. lpNet: a linear programming approach to reconstruct signal transduction networks.

    Science.gov (United States)

    Matos, Marta R A; Knapp, Bettina; Kaderali, Lars

    2015-10-01

    With the widespread availability of high-throughput experimental technologies it has become possible to study hundreds to thousands of cellular factors simultaneously, such as coding- or non-coding mRNA or protein concentrations. Still, extracting information about the underlying regulatory or signaling interactions from these data remains a difficult challenge. We present a flexible approach towards network inference based on linear programming. Our method reconstructs the interactions of factors from a combination of perturbation/non-perturbation and steady-state/time-series data. We show both on simulated and real data that our methods are able to reconstruct the underlying networks fast and efficiently, thus shedding new light on biological processes and, in particular, into disease's mechanisms of action. We have implemented the approach as an R package available through bioconductor. This R package is freely available under the Gnu Public License (GPL-3) from bioconductor.org (http://bioconductor.org/packages/release/bioc/html/lpNet.html) and is compatible with most operating systems (Windows, Linux, Mac OS) and hardware architectures. bettina.knapp@helmholtz-muenchen.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  8. Security for 4G and 5G Cellular Networks: A Survey of Existing Authentication and Privacy-preserving Schemes

    OpenAIRE

    Ferrag, Mohamed Amine; Maglaras, Leandros; Argyriou, Antonios; Kosmanos, Dimitrios; Janicke, Helge

    2017-01-01

    This paper presents a comprehensive survey of existing authentication and privacy-preserving schemes for 4G and 5G cellular networks. We start by providing an overview of existing surveys that deal with 4G and 5G communications, applications, standardization, and security. Then, we give a classification of threat models in 4G and 5G cellular networks in four categories, including, attacks against privacy, attacks against integrity, attacks against availability, and attacks against authenticat...

  9. CNNs for sinusoidal signal recognition in hearing rehabilitation

    Science.gov (United States)

    Carnimeo, Leonarda; Giaquinto, Antonio

    2003-04-01

    In this paper, a contribution is given to provide a tool to the recognition of sinusoidal signals with a particular reference to the field of pediatric hearing rehabilitation. To this purpose, a synthesis technique previously developed by the authors' is used to design a Cellular Neural Network for an Associative Memory able to compare submitted discrete-time sinusoidal signals with memorized ones. A robustness analysis of the synthesized associative memory is also developed both for noisy inputs and for parameter variations. Simulation results are then reported to illustrate the performances of the designed network.

  10. Cellular Neural Networks: A genetic algorithm for parameters optimization in artificial vision applications

    International Nuclear Information System (INIS)

    Taraglio, S.; Zanela, A.

    1997-03-01

    An optimization method for some of the CNN's (Cellular Neural Network) parameters, based on evolutionary strategies, is proposed. The new class of feedback template found is more effective in extracting features from the images that an autonomous vehicle acquires, than in the previous CNN's literature

  11. Optical Performance Monitoring and Signal Optimization in Optical Networks

    DEFF Research Database (Denmark)

    Petersen, Martin Nordal

    2006-01-01

    The thesis studies performance monitoring for the next generation optical networks. The focus is on all-optical networks with bit-rates of 10 Gb/s or above. Next generation all-optical networks offer large challenges as the optical transmitted distance increases and the occurrence of electrical-optical......-electrical regeneration points decreases. This thesis evaluates the impact of signal degrading effects that are becoming of increasing concern in all-optical high-speed networks due to all-optical switching and higher bit-rates. Especially group-velocity-dispersion (GVD) and a number of nonlinear effects will require...... enhanced attention to avoid signal degradations. The requirements for optical performance monitoring features are discussed, and the thesis evaluates the advantages and necessity of increasing the level of performance monitoring parameters in the physical layer. In particular, methods for optical...

  12. Mobile Position Estimation using Artificial Neural Network in CDMA Cellular Systems

    Directory of Open Access Journals (Sweden)

    Omar Waleed Abdulwahhab

    2017-01-01

    Full Text Available Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA and received signal strength (RSS are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The results show that the neural network has good performance compared with two other analytical methods which are average positioning method and optimal positioning method.

  13. OPNET simulation Signaling System No.7 (SS7) network interfaces

    OpenAIRE

    Ow, Kong Chung.

    2000-01-01

    This thesis presents an OPNET model and simulation of the Signaling System No.7 (SS7) network, which is dubbed the world's largest data communications network. The main focus of the study is to model one of its levels, the Message Transfer Part Level 3, in accordance with the ITU.T recommendation Q.704. An overview of SS7 that includes the evolution and basics of SS7 architecture is provided to familarize the reader with the topic. This includes the protocol stack, signaling points, signaling...

  14. Control of fluxes in metabolic networks

    Science.gov (United States)

    Basler, Georg; Nikoloski, Zoran; Larhlimi, Abdelhalim; Barabási, Albert-László; Liu, Yang-Yu

    2016-01-01

    Understanding the control of large-scale metabolic networks is central to biology and medicine. However, existing approaches either require specifying a cellular objective or can only be used for small networks. We introduce new coupling types describing the relations between reaction activities, and develop an efficient computational framework, which does not require any cellular objective for systematic studies of large-scale metabolism. We identify the driver reactions facilitating control of 23 metabolic networks from all kingdoms of life. We find that unicellular organisms require a smaller degree of control than multicellular organisms. Driver reactions are under complex cellular regulation in Escherichia coli, indicating their preeminent role in facilitating cellular control. In human cancer cells, driver reactions play pivotal roles in malignancy and represent potential therapeutic targets. The developed framework helps us gain insights into regulatory principles of diseases and facilitates design of engineering strategies at the interface of gene regulation, signaling, and metabolism. PMID:27197218

  15. Dominating biological networks.

    Directory of Open Access Journals (Sweden)

    Tijana Milenković

    Full Text Available Proteins are essential macromolecules of life that carry out most cellular processes. Since proteins aggregate to perform function, and since protein-protein interaction (PPI networks model these aggregations, one would expect to uncover new biology from PPI network topology. Hence, using PPI networks to predict protein function and role of protein pathways in disease has received attention. A debate remains open about whether network properties of "biologically central (BC" genes (i.e., their protein products, such as those involved in aging, cancer, infectious diseases, or signaling and drug-targeted pathways, exhibit some topological centrality compared to the rest of the proteins in the human PPI network.To help resolve this debate, we design new network-based approaches and apply them to get new insight into biological function and disease. We hypothesize that BC genes have a topologically central (TC role in the human PPI network. We propose two different concepts of topological centrality. We design a new centrality measure to capture complex wirings of proteins in the network that identifies as TC those proteins that reside in dense extended network neighborhoods. Also, we use the notion of domination and find dominating sets (DSs in the PPI network, i.e., sets of proteins such that every protein is either in the DS or is a neighbor of the DS. Clearly, a DS has a TC role, as it enables efficient communication between different network parts. We find statistically significant enrichment in BC genes of TC nodes and outperform the existing methods indicating that genes involved in key biological processes occupy topologically complex and dense regions of the network and correspond to its "spine" that connects all other network parts and can thus pass cellular signals efficiently throughout the network. To our knowledge, this is the first study that explores domination in the context of PPI networks.

  16. Mathematical modelling of SERK mediated BR signalling

    NARCIS (Netherlands)

    Esse, van G.W.

    2013-01-01

    Being sessile by nature plants are continuously challenged by biotic and abiotic stress factors. At the cellular level, different stimuli are perceived and translated to the desired response. In order to achieve this, signal transduction cascades have to be interlinked. Complex networks

  17. Bluetooth telemedicine processor for multichannel biomedical signal transmission via mobile cellular networks.

    Science.gov (United States)

    Rasid, Mohd Fadlee A; Woodward, Bryan

    2005-03-01

    One of the emerging issues in m-Health is how best to exploit the mobile communications technologies that are now almost globally available. The challenge is to produce a system to transmit a patient's biomedical signals directly to a hospital for monitoring or diagnosis, using an unmodified mobile telephone. The paper focuses on the design of a processor, which samples signals from sensors on the patient. It then transmits digital data over a Bluetooth link to a mobile telephone that uses the General Packet Radio Service. The modular design adopted is intended to provide a "future-proofed" system, whose functionality may be upgraded by modifying the software.

  18. Kinome-wide Decoding of Network-Attacking Mutations Rewiring Cancer Signaling

    DEFF Research Database (Denmark)

    Creixell, Pau; Schoof, Erwin M; Simpson, Craig D.

    2015-01-01

    Cancer cells acquire pathological phenotypes through accumulation of mutations that perturb signaling networks. However, global analysis of these events is currently limited. Here, we identify six types of network-attacking mutations (NAMs), including changes in kinase and SH2 modulation, network...... and experimentally validated several NAMs, including PKCγ M501I and PKD1 D665N, which encode specificity switches analogous to the appearance of kinases de novo within the kinome. We discover mutant molecular logic gates, a drift toward phospho-threonine signaling, weakening of phosphorylation motifs, and kinase...

  19. Cellular Neural Networks: A genetic algorithm for parameters optimization in artificial vision applications

    Energy Technology Data Exchange (ETDEWEB)

    Taraglio, S. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dipt. Innovazione; Zanela, A. [Rome Univ. `La Sapienza` (Italy). Dipt. di Fisica

    1997-03-01

    An optimization method for some of the CNN`s (Cellular Neural Network) parameters, based on evolutionary strategies, is proposed. The new class of feedback template found is more effective in extracting features from the images that an autonomous vehicle acquires, than in the previous CNN`s literature.

  20. Delay-dependent exponential stability of cellular neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Zhang Qiang; Wei Xiaopeng; Xu Jin

    2005-01-01

    The global exponential stability of cellular neural networks (CNNs) with time-varying delays is analyzed. Two new sufficient conditions ensuring global exponential stability for delayed CNNs are obtained. The conditions presented here are related to the size of delay. The stability results improve the earlier publications. Two examples are given to demonstrate the effectiveness of the obtained results

  1. In-Band Full-Duplex Communications for Cellular Networks with Partial Uplink/Downlink Overlap

    KAUST Repository

    Alammouri, Ahmad; Elsawy, Hesham; Amin, Osama; Alouini, Mohamed-Slim

    2015-01-01

    In-band full-duplex (FD) communications have been optimistically promoted to improve the spectrum utilization in cellular networks. However, the explicit impact of spatial interference, imposed by FD communications, on uplink and downlink transmissions has been overlooked in the literature. This paper presents an extensive study of the explicit effect of FD communications on the uplink and downlink performances. For the sake of rigorous analysis, we develop a tractable framework based on stochastic geometry toolset. The developed model accounts for uplink truncated channel inversion power control in FD cellular networks. The study shows that FD communications improve the downlink throughput at the expense of significant degradation in the uplink throughput. Therefore, we propose a novel fine-grained duplexing scheme, denoted as α-duplex scheme, which allows a partial overlap between uplink and downlink frequency bands. To this end, we show that the amount of the overlap can be optimized via adjusting α to achieve a certain design objective.

  2. In-Band Full-Duplex Communications for Cellular Networks with Partial Uplink/Downlink Overlap

    KAUST Repository

    AlAmmouri, Ahmad

    2015-12-06

    In-band full-duplex (FD) communications have been optimistically promoted to improve the spectrum utilization in cellular networks. However, the explicit impact of spatial interference, imposed by FD communications, on uplink and downlink transmissions has been overlooked in the literature. This paper presents an extensive study of the explicit effect of FD communications on the uplink and downlink performances. For the sake of rigorous analysis, we develop a tractable framework based on stochastic geometry toolset. The developed model accounts for uplink truncated channel inversion power control in FD cellular networks. The study shows that FD communications improve the downlink throughput at the expense of significant degradation in the uplink throughput. Therefore, we propose a novel fine-grained duplexing scheme, denoted as α-duplex scheme, which allows a partial overlap between uplink and downlink frequency bands. To this end, we show that the amount of the overlap can be optimized via adjusting α to achieve a certain design objective.

  3. Systematic network assessment of the carcinogenic activities of cadmium

    International Nuclear Information System (INIS)

    Chen, Peizhan; Duan, Xiaohua; Li, Mian; Huang, Chao; Li, Jingquan; Chu, Ruiai; Ying, Hao; Song, Haiyun; Jia, Xudong; Ba, Qian; Wang, Hui

    2016-01-01

    Cadmium has been defined as type I carcinogen for humans, but the underlying mechanisms of its carcinogenic activity and its influence on protein-protein interactions in cells are not fully elucidated. The aim of the current study was to evaluate, systematically, the carcinogenic activity of cadmium with systems biology approaches. From a literature search of 209 studies that performed with cellular models, 208 proteins influenced by cadmium exposure were identified. All of these were assessed by Western blotting and were recognized as key nodes in network analyses. The protein-protein functional interaction networks were constructed with NetBox software and visualized with Cytoscape software. These cadmium-rewired genes were used to construct a scale-free, highly connected biological protein interaction network with 850 nodes and 8770 edges. Of the network, nine key modules were identified and 60 key signaling pathways, including the estrogen, RAS, PI3K-Akt, NF-κB, HIF-1α, Jak-STAT, and TGF-β signaling pathways, were significantly enriched. With breast cancer, colorectal and prostate cancer cellular models, we validated the key node genes in the network that had been previously reported or inferred form the network by Western blotting methods, including STAT3, JNK, p38, SMAD2/3, P65, AKT1, and HIF-1α. These results suggested the established network was robust and provided a systematic view of the carcinogenic activities of cadmium in human. - Highlights: • A cadmium-influenced network with 850 nodes and 8770 edges was established. • The cadmium-rewired gene network was scale-free and highly connected. • Nine modules were identified, and 60 key signaling pathways related to cadmium-induced carcinogenesis were found. • Key mediators in the network were validated in multiple cellular models.

  4. Systematic network assessment of the carcinogenic activities of cadmium

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Peizhan; Duan, Xiaohua; Li, Mian; Huang, Chao [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Li, Jingquan; Chu, Ruiai; Ying, Hao; Song, Haiyun [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Jia, Xudong [Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Ba, Qian, E-mail: qba@sibs.ac.cn [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wang, Hui, E-mail: huiwang@sibs.ac.cn [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); School of Life Science and Technology, ShanghaiTech University, Shanghai (China)

    2016-11-01

    Cadmium has been defined as type I carcinogen for humans, but the underlying mechanisms of its carcinogenic activity and its influence on protein-protein interactions in cells are not fully elucidated. The aim of the current study was to evaluate, systematically, the carcinogenic activity of cadmium with systems biology approaches. From a literature search of 209 studies that performed with cellular models, 208 proteins influenced by cadmium exposure were identified. All of these were assessed by Western blotting and were recognized as key nodes in network analyses. The protein-protein functional interaction networks were constructed with NetBox software and visualized with Cytoscape software. These cadmium-rewired genes were used to construct a scale-free, highly connected biological protein interaction network with 850 nodes and 8770 edges. Of the network, nine key modules were identified and 60 key signaling pathways, including the estrogen, RAS, PI3K-Akt, NF-κB, HIF-1α, Jak-STAT, and TGF-β signaling pathways, were significantly enriched. With breast cancer, colorectal and prostate cancer cellular models, we validated the key node genes in the network that had been previously reported or inferred form the network by Western blotting methods, including STAT3, JNK, p38, SMAD2/3, P65, AKT1, and HIF-1α. These results suggested the established network was robust and provided a systematic view of the carcinogenic activities of cadmium in human. - Highlights: • A cadmium-influenced network with 850 nodes and 8770 edges was established. • The cadmium-rewired gene network was scale-free and highly connected. • Nine modules were identified, and 60 key signaling pathways related to cadmium-induced carcinogenesis were found. • Key mediators in the network were validated in multiple cellular models.

  5. Signal Transduction Pathways of TNAP: Molecular Network Analyses.

    Science.gov (United States)

    Négyessy, László; Györffy, Balázs; Hanics, János; Bányai, Mihály; Fonta, Caroline; Bazsó, Fülöp

    2015-01-01

    Despite the growing body of evidence pointing on the involvement of tissue non-specific alkaline phosphatase (TNAP) in brain function and diseases like epilepsy and Alzheimer's disease, our understanding about the role of TNAP in the regulation of neurotransmission is severely limited. The aim of our study was to integrate the fragmented knowledge into a comprehensive view regarding neuronal functions of TNAP using objective tools. As a model we used the signal transduction molecular network of a pyramidal neuron after complementing with TNAP related data and performed the analysis using graph theoretic tools. The analyses show that TNAP is in the crossroad of numerous pathways and therefore is one of the key players of the neuronal signal transduction network. Through many of its connections, most notably with molecules of the purinergic system, TNAP serves as a controller by funnelling signal flow towards a subset of molecules. TNAP also appears as the source of signal to be spread via interactions with molecules involved among others in neurodegeneration. Cluster analyses identified TNAP as part of the second messenger signalling cascade. However, TNAP also forms connections with other functional groups involved in neuronal signal transduction. The results indicate the distinct ways of involvement of TNAP in multiple neuronal functions and diseases.

  6. Variability of signal-to-noise ratio and the network analysis of gravitational wave burst signals

    International Nuclear Information System (INIS)

    Mohanty, S D; Rakhmanov, M; Klimenko, S; Mitselmakher, G

    2006-01-01

    The detection and estimation of gravitational wave burst signals, with a priori unknown polarization waveforms, requires the use of data from a network of detectors. Maximizing the network likelihood functional over all waveforms and sky positions yields point estimates for them as well as a detection statistic. However, the transformation from the data to estimates can become ill-conditioned over parts of the sky, resulting in significant errors in estimation. We modify the likelihood procedure by introducing a penalty functional which suppresses candidate solutions that display large signal-to-noise ratio (SNR) variability as the source is displaced on the sky. Simulations show that the resulting network analysis method performs significantly better in estimating the sky position of a source. Further, this method can be applied to any network, irrespective of the number or mutual alignment of detectors

  7. Modeling Cellular Networks with Full Duplex D2D Communication: A Stochastic Geometry Approach

    KAUST Repository

    Ali, Konpal S.

    2016-08-24

    Full-duplex (FD) communication is optimistically promoted to double the spectral efficiency if sufficient self-interference cancellation (SIC) is achieved. However, this is not true when deploying FD-communication in a large-scale setup due to the induced mutual interference. Therefore, a large-scale study is necessary to draw legitimate conclusions about gains associated with FD-communication. This paper studies the FD operation for underlay device-to-device (D2D) communication sharing the uplink resources in cellular networks. We propose a disjoint fine-tuned selection criterion for the D2D and FD modes of operation. Then, we develop a tractable analytical paradigm, based on stochastic geometry, to calculate the outage probability and rate for cellular and D2D users. The results reveal that even in the case of perfect SIC, due to the increased interference injected to the network by FD-D2D communication, having all proximity UEs transmit in FD-D2D is not beneficial for the network. However, if the system parameters are carefully tuned, non-trivial network spectral-efficiency gains (64% shown) can be harvested. We also investigate the effects of imperfect SIC and D2D-link distance distribution on the harvested FD gains.

  8. Hybrid digital signal processing and neural networks applications in PWRs

    International Nuclear Information System (INIS)

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-01-01

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications

  9. Service-Aware Retransmission Control in Cellular Networks

    Directory of Open Access Journals (Sweden)

    Nadhir Ben Halima

    2010-01-01

    Full Text Available This paper proposes a service-aware cross-layer approach between application/transport layers on the mobile terminal and link layer on the wireless base station to enable dynamic control on the level of per-packet error protection for multimedia data streams. Specifically, in the context of cellular networks, the proposed scheme enables the mobile terminal to specify to the base station the desired level of Hybrid ARQ (HARQ protection by using an in-band control feedback channel. Such protection is dynamically adapted on a per-packet basis and depends on the perceptual importance of different packets as well as on the reception history of the flow. Experimental results demonstrate the potential benefits deriving from the proposed strategy either for audio and video real-time streams as well as for TCP-based data transfers.

  10. Applying Statistical and Complex Network Methods to Explore the Key Signaling Molecules of Acupuncture Regulating Neuroendocrine-Immune Network

    Directory of Open Access Journals (Sweden)

    Kuo Zhang

    2018-01-01

    Full Text Available The mechanisms of acupuncture are still unclear. In order to reveal the regulatory effect of manual acupuncture (MA on the neuroendocrine-immune (NEI network and identify the key signaling molecules during MA modulating NEI network, we used a rat complete Freund’s adjuvant (CFA model to observe the analgesic and anti-inflammatory effect of MA, and, what is more, we used statistical and complex network methods to analyze the data about the expression of 55 common signaling molecules of NEI network in ST36 (Zusanli acupoint, and serum and hind foot pad tissue. The results indicate that MA had significant analgesic, anti-inflammatory effects on CFA rats; the key signaling molecules may play a key role during MA regulating NEI network, but further research is needed.

  11. Digital Signal Processing for a Sliceable Transceiver for Optical Access Networks

    DEFF Research Database (Denmark)

    Saldaña Cercos, Silvia; Wagner, Christoph; Vegas Olmos, Juan José

    2015-01-01

    Methods to upgrade the network infrastructure to cope with current traffic demands has attracted increasing research efforts. A promising alternative is signal slicing. Signal slicing aims at re-using low bandwidth equipment to satisfy high bandwidth traffic demands. This technique has been used...... also for implementing full signal path symmetry in real-time oscilloscopes to provide performance and signal fidelity (i.e. lower noise and jitter). In this paper the key digital signal processing (DSP) subsystems required to achieve signal slicing are surveyed. It also presents, for the first time...... penalty is reported for 10 Gbps. Power savings of the order of hundreds of Watts can be obtained when using signal slicing as an alternative to 10 Gbps implemented access networks....

  12. Digital Signal Processing and Control for the Study of Gene Networks

    Science.gov (United States)

    Shin, Yong-Jun

    2016-04-01

    Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.

  13. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    NARCIS (Netherlands)

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2016-01-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide (≈ 35 500 km2) 15 min rainfall maps can

  14. Generation and comprehensive analysis of an influenza virus polymerase cellular interaction network.

    Science.gov (United States)

    Tafforeau, Lionel; Chantier, Thibault; Pradezynski, Fabrine; Pellet, Johann; Mangeot, Philippe E; Vidalain, Pierre-Olivier; Andre, Patrice; Rabourdin-Combe, Chantal; Lotteau, Vincent

    2011-12-01

    The influenza virus transcribes and replicates its genome inside the nucleus of infected cells. Both activities are performed by the viral RNA-dependent RNA polymerase that is composed of the three subunits PA, PB1, and PB2, and recent studies have shown that it requires host cell factors to transcribe and replicate the viral genome. To identify these cellular partners, we generated a comprehensive physical interaction map between each polymerase subunit and the host cellular proteome. A total of 109 human interactors were identified by yeast two-hybrid screens, whereas 90 were retrieved by literature mining. We built the FluPol interactome network composed of the influenza virus polymerase (PA, PB1, and PB2) and the nucleoprotein NP and 234 human proteins that are connected through 279 viral-cellular protein interactions. Analysis of this interactome map revealed enriched cellular functions associated with the influenza virus polymerase, including host factors involved in RNA polymerase II-dependent transcription and mRNA processing. We confirmed that eight influenza virus polymerase-interacting proteins are required for virus replication and transcriptional activity of the viral polymerase. These are involved in cellular transcription (C14orf166, COPS5, MNAT1, NMI, and POLR2A), translation (EIF3S6IP), nuclear transport (NUP54), and DNA repair (FANCG). Conversely, we identified PRKRA, which acts as an inhibitor of the viral polymerase transcriptional activity and thus is required for the cellular antiviral response.

  15. Overload Control in a SIP Signaling Network

    OpenAIRE

    Masataka Ohta

    2007-01-01

    The Internet telephony employs a new type of Internet communication on which a mutual communication is realized by establishing sessions. Session Initiation Protocol (SIP) is used to establish sessions between end-users. For unreliable transmission (UDP), SIP message should be retransmitted when it is lost. The retransmissions increase a load of the SIP signaling network, and sometimes lead to performance degradation when a network is overloaded. The paper proposes an overload control for a S...

  16. Cellular computational generalized neuron network for frequency situational intelligence in a multi-machine power system.

    Science.gov (United States)

    Wei, Yawei; Venayagamoorthy, Ganesh Kumar

    2017-09-01

    To prevent large interconnected power system from a cascading failure, brownout or even blackout, grid operators require access to faster than real-time information to make appropriate just-in-time control decisions. However, the communication and computational system limitations of currently used supervisory control and data acquisition (SCADA) system can only deliver delayed information. However, the deployment of synchrophasor measurement devices makes it possible to capture and visualize, in near-real-time, grid operational data with extra granularity. In this paper, a cellular computational network (CCN) approach for frequency situational intelligence (FSI) in a power system is presented. The distributed and scalable computing unit of the CCN framework makes it particularly flexible for customization for a particular set of prediction requirements. Two soft-computing algorithms have been implemented in the CCN framework: a cellular generalized neuron network (CCGNN) and a cellular multi-layer perceptron network (CCMLPN), for purposes of providing multi-timescale frequency predictions, ranging from 16.67 ms to 2 s. These two developed CCGNN and CCMLPN systems were then implemented on two different scales of power systems, one of which installed a large photovoltaic plant. A real-time power system simulator at weather station within the Real-Time Power and Intelligent Systems (RTPIS) laboratory at Clemson, SC, was then used to derive typical FSI results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Sensor signal analysis by neural networks for surveillance in nuclear reactors

    International Nuclear Information System (INIS)

    Keyvan, S.; Rabelo, L.C.

    1992-01-01

    The application of neural networks as a tool for reactor diagnostics is examined here. Reactor pump signals utilized in a wear-out monitoring system developed for early detection of the degradation of a pump shaft are analyzed as a semi-benchmark test to study the feasibility of neural networks for monitoring and surveillance in nuclear reactors. The Adaptive Resonance Theory (ART 2 and ART 2-A) paradigm of neural networks is applied in this study. The signals are collected signals as well as generated signals simulating the wear progress. The wear-out monitoring system applies noise analysis techniques, and is capable of distinguishing these signals apart and providing a measure of the progress of the degradation. This paper presents the results of the analysis of these data, and provides an evaluation on the performance of ART 2-A and ART 2 for reactor signal analysis. The selection of ART 2 is due to its desired design principles such as unsupervised learning, stability-plasticity, search-direct access, and the match-reset tradeoffs

  18. Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6.

    Science.gov (United States)

    Samuelraj, Ananthi Jebaseeli; Jayapal, Sundararajan

    2015-01-01

    Proxy Mobile IPV6 (PMIPV6) is a network based mobility management protocol which supports node's mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO) in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node's mobility should be modified to support group nodes' mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point.

  19. Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6

    Directory of Open Access Journals (Sweden)

    Ananthi Jebaseeli Samuelraj

    2015-01-01

    Full Text Available Proxy Mobile IPV6 (PMIPV6 is a network based mobility management protocol which supports node’s mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node’s mobility should be modified to support group nodes’ mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point.

  20. Applications of autoassociative neural networks for signal validation in accident management

    International Nuclear Information System (INIS)

    Fantoni, P.; Mazzola, A.

    1994-01-01

    The OECD Halden Reactor Project has been working for several years with computer based systems for determination on plant status including early fault detection and signal validation. The method here presented explores the possibility to use a neural network approach to validate important process signals during normal and abnormal plant conditions. In BWR plants, signal validation has two important applications: reliable thermal limits calculation and reliable inputs to other computerized systems that support the operator during accident scenarious. This work shows how a properly trained autoassociative neural network can promptly detect faulty process signal measurements and produce a best estimate of the actual process value. Noise has been artificially added to the input to evaluate the network ability to respond in a very low signal to noise ratio environment. Training and test datasets have been simulated by the real time transient simulator code APROS. Future development addresses the validation of the model through the use of real data from the plant. (author). 5 refs, 17 figs

  1. Multiple-failure signal validation in nuclear power plants using artificial neural networks

    International Nuclear Information System (INIS)

    Fantoni, P.F.; Mazzola, A.

    1996-01-01

    The possibility of using a neural network to validate process signals during normal and abnormal plant conditions is explored. In boiling water reactor plants, signal validation is used to generate reliable thermal limits calculation and to supply reliable inputs to other computerized systems that support the operator during accident scenarios. The way that autoassociative neural networks can promptly detect faulty process signal measurements and produce a best estimate of the actual process values even in multifailure situations is shown. A method was developed to train the network for multiple sensor-failure detection, based on a random failure simulation algorithm. Noise was artificially added to the input to evaluate the network's ability to respond in a very low signal-to-noise ratio environment. Training and test data sets were simulated by the real-time transient simulator code APROS

  2. Phase transitions in pancreatic islet cellular networks and implications for type-1 diabetes

    Science.gov (United States)

    Stamper, I. J.; Jackson, Elais; Wang, Xujing

    2014-01-01

    In many aspects the onset of a chronic disease resembles a phase transition in a complex dynamic system: Quantitative changes accumulate largely unnoticed until a critical threshold is reached, which causes abrupt qualitative changes of the system. In this study we examine a special case, the onset of type-1 diabetes (T1D), a disease that results from loss of the insulin-producing pancreatic islet β cells. Within each islet, the β cells are electrically coupled to each other via gap-junctional channels. This intercellular coupling enables the β cells to synchronize their insulin release, thereby generating the multiscale temporal rhythms in blood insulin that are critical to maintaining blood glucose homeostasis. Using percolation theory we show how normal islet function is intrinsically linked to network connectivity. In particular, the critical amount of β-cell death at which the islet cellular network loses site percolation is consistent with laboratory and clinical observations of the threshold loss of β cells that causes islet functional failure. In addition, numerical simulations confirm that the islet cellular network needs to be percolated for β cells to synchronize. Furthermore, the interplay between site percolation and bond strength predicts the existence of a transient phase of islet functional recovery after onset of T1D and introduction of treatment, potentially explaining the honeymoon phenomenon. Based on these results, we hypothesize that the onset of T1D may be the result of a phase transition of the islet β-cell network.

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

    Science.gov (United States)

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

    2016-09-23

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

  4. Cluster synchronization transmission of different external signals in discrete uncertain network

    Science.gov (United States)

    Li, Chengren; Lü, Ling; Chen, Liansong; Hong, Yixuan; Zhou, Shuang; Yang, Yiming

    2018-07-01

    We research cluster synchronization transmissions of different external signals in discrete uncertain network. Based on the Lyapunov theorem, the network controller and the identification law of uncertain adjustment parameter are designed, and they are efficiently used to achieve the cluster synchronization and the identification of uncertain adjustment parameter. In our technical scheme, the network nodes in each cluster and the transmitted external signal can be different, and they allow the presence of uncertain parameters in the network. Especially, we are free to choose the clustering topologies, the cluster number and the node number in each cluster.

  5. Towards the systematic discovery of signal transduction networks using phosphorylation dynamics data

    Directory of Open Access Journals (Sweden)

    Yachie Nozomu

    2010-05-01

    Full Text Available Abstract Background Phosphorylation is a ubiquitous and fundamental regulatory mechanism that controls signal transduction in living cells. The number of identified phosphoproteins and their phosphosites is rapidly increasing as a result of recent mass spectrometry-based approaches. Results We analyzed time-course phosphoproteome data obtained previously by liquid chromatography mass spectrometry with the stable isotope labeling using amino acids in cell culture (SILAC method. This provides the relative phosphorylation activities of digested peptides at each of five time points after stimulating HeLa cells with epidermal growth factor (EGF. We initially calculated the correlations between the phosphorylation dynamics patterns of every pair of peptides and connected the strongly correlated pairs to construct a network. We found that peptides extracted from the same intracellular fraction (nucleus vs. cytoplasm tended to be close together within this phosphorylation dynamics-based network. The network was then analyzed using graph theory and compared with five known signal-transduction pathways. The dynamics-based network was correlated with known signaling pathways in the NetPath and Phospho.ELM databases, and especially with the EGF receptor (EGFR signaling pathway. Although the phosphorylation patterns of many proteins were drastically changed by the EGF stimulation, our results suggest that only EGFR signaling transduction was both strongly activated and precisely controlled. Conclusions The construction of a phosphorylation dynamics-based network provides a useful overview of condition-specific intracellular signal transduction using quantitative time-course phosphoproteome data under specific experimental conditions. Detailed prediction of signal transduction based on phosphoproteome dynamics remains challenging. However, since the phosphorylation profiles of kinase-substrate pairs on the specific pathway were localized in the dynamics

  6. Wireless Cellular Mobile Communications

    OpenAIRE

    Zalud, V.

    2002-01-01

    In this article is briefly reviewed the history of wireless cellular mobile communications, examined the progress in current second generation (2G) cellular standards and discussed their migration to the third generation (3G). The European 2G cellular standard GSM and its evolution phases GPRS and EDGE are described somewhat in detail. The third generation standard UMTS taking up on GSM/GPRS core network and equipped with a new advanced access network on the basis of code division multiple ac...

  7. Energy-efficient power control for OFDMA cellular networks

    KAUST Repository

    Sboui, Lokman

    2016-12-24

    In this paper, we study the energy efficiency (EE) of orthogonal frequency-division multiple access (OFDMA) cellular networks. Our objective is to present a power allocation scheme that maximizes the EE of downlink communications. We propose a novel explicit expression of the optimal power allocation to each subcarrier. We also present the power control when the transmit power is limited by power budget constraint or/and minimal rate constraint and we highlight the occurrence of some transmission outage events depending on the constraints\\' parameters. In the numerical results, we show that our proposed power control improves the EE especially at high power budget regime and low minimal rate regime. In addition, we show that having a higher number of subcarriers enhances the OFDMA EE.

  8. Analysis of FOXO transcriptional networks

    NARCIS (Netherlands)

    van der Vos, K.E.

    2010-01-01

    The PI3K-PKB-FOXO signalling module plays a pivotal role in a wide variety of cellular processes, including proliferation, survival, differentiation and metabolism. Inappropriate activation of this network is frequently observed in human cancer and causes uncontrolled proliferation and survival. In

  9. Cellular compartments cause multistability and allow cells to process more information

    DEFF Research Database (Denmark)

    Harrington, Heather A; Feliu, Elisenda; Wiuf, Carsten

    2013-01-01

    recent developments from dynamical systems and chemical reaction network theory to identify and characterize the key-role of the spatial organization of eukaryotic cells in cellular information processing. In particular, the existence of distinct compartments plays a pivotal role in whether a system...... is capable of multistationarity (multiple response states), and is thus directly linked to the amount of information that the signaling molecules can represent in the nucleus. Multistationarity provides a mechanism for switching between different response states in cell signaling systems and enables multiple...

  10. Global exponential stability of cellular neural networks with continuously distributed delays and impulses

    International Nuclear Information System (INIS)

    Wang Yixuan; Xiong Wanmin; Zhou Qiyuan; Xiao Bing; Yu Yuehua

    2006-01-01

    In this Letter cellular neural networks with continuously distributed delays and impulses are considered. Sufficient conditions for the existence and global exponential stability of a unique equilibrium point are established by using the fixed point theorem and differential inequality techniques. The results of this Letter are new and they complement previously known results

  11. A Time-Varied Probabilistic ON/OFF Switching Algorithm for Cellular Networks

    KAUST Repository

    Rached, Nadhir B.; Ghazzai, Hakim; Kadri, Abdullah; Alouini, Mohamed-Slim

    2018-01-01

    In this letter, we develop a time-varied probabilistic on/off switching planning method for cellular networks to reduce their energy consumption. It consists in a risk-aware optimization approach that takes into consideration the randomness of the user profile associated with each base station (BS). The proposed approach jointly determines (i) the instants of time at which the current active BS configuration must be updated due to an increase or decrease of the network traffic load, and (ii) the set of minimum BSs to be activated to serve the networks’ subscribers. Probabilistic metrics modeling the traffic profile variation are developed to trigger this dynamic on/off switching operation. Selected simulation results are then performed to validate the proposed algorithm for different system parameters.

  12. A Time-Varied Probabilistic ON/OFF Switching Algorithm for Cellular Networks

    KAUST Repository

    Rached, Nadhir B.

    2018-01-11

    In this letter, we develop a time-varied probabilistic on/off switching planning method for cellular networks to reduce their energy consumption. It consists in a risk-aware optimization approach that takes into consideration the randomness of the user profile associated with each base station (BS). The proposed approach jointly determines (i) the instants of time at which the current active BS configuration must be updated due to an increase or decrease of the network traffic load, and (ii) the set of minimum BSs to be activated to serve the networks’ subscribers. Probabilistic metrics modeling the traffic profile variation are developed to trigger this dynamic on/off switching operation. Selected simulation results are then performed to validate the proposed algorithm for different system parameters.

  13. Molecular signaling involving intrinsically disordered proteins in prostate cancer

    Directory of Open Access Journals (Sweden)

    Anna Russo

    2016-01-01

    Full Text Available Investigations on cellular protein interaction networks (PINs reveal that proteins that constitute hubs in a PIN are notably enriched in Intrinsically Disordered Proteins (IDPs compared to proteins that constitute edges, highlighting the role of IDPs in signaling pathways. Most IDPs rapidly undergo disorder-to-order transitions upon binding to their biological targets to perform their function. Conformational dynamics enables IDPs to be versatile and to interact with a broad range of interactors under normal physiological conditions where their expression is tightly modulated. IDPs are involved in many cellular processes such as cellular signaling, transcriptional regulation, and splicing; thus, their high-specificity/low-affinity interactions play crucial roles in many human diseases including cancer. Prostate cancer (PCa is one of the leading causes of cancer-related mortality in men worldwide. Therefore, identifying molecular mechanisms of the oncogenic signaling pathways that are involved in prostate carcinogenesis is crucial. In this review, we focus on the aspects of cellular pathways leading to PCa in which IDPs exert a primary role.

  14. Predictive model identifies key network regulators of cardiomyocyte mechano-signaling.

    Directory of Open Access Journals (Sweden)

    Philip M Tan

    2017-11-01

    Full Text Available Mechanical strain is a potent stimulus for growth and remodeling in cells. Although many pathways have been implicated in stretch-induced remodeling, the control structures by which signals from distinct mechano-sensors are integrated to modulate hypertrophy and gene expression in cardiomyocytes remain unclear. Here, we constructed and validated a predictive computational model of the cardiac mechano-signaling network in order to elucidate the mechanisms underlying signal integration. The model identifies calcium, actin, Ras, Raf1, PI3K, and JAK as key regulators of cardiac mechano-signaling and characterizes crosstalk logic imparting differential control of transcription by AT1R, integrins, and calcium channels. We find that while these regulators maintain mostly independent control over distinct groups of transcription factors, synergy between multiple pathways is necessary to activate all the transcription factors necessary for gene transcription and hypertrophy. We also identify a PKG-dependent mechanism by which valsartan/sacubitril, a combination drug recently approved for treating heart failure, inhibits stretch-induced hypertrophy, and predict further efficacious pairs of drug targets in the network through a network-wide combinatorial search.

  15. Seismic signal auto-detecing from different features by using Convolutional Neural Network

    Science.gov (United States)

    Huang, Y.; Zhou, Y.; Yue, H.; Zhou, S.

    2017-12-01

    We try Convolutional Neural Network to detect some features of seismic data and compare their efficience. The features include whether a signal is seismic signal or noise and the arrival time of P and S phase and each feature correspond to a Convolutional Neural Network. We first use traditional STA/LTA to recongnize some events and then use templete matching to find more events as training set for the Neural Network. To make the training set more various, we add some noise to the seismic data and make some synthetic seismic data and noise. The 3-component raw signal and time-frequancy ananlyze are used as the input data for our neural network. Our Training is performed on GPUs to achieve efficient convergence. Our method improved the precision in comparison with STA/LTA and template matching. We will move to recurrent neural network to see if this kind network is better in detect P and S phase.

  16. Simultaneous multichannel signal transfers via chaos in a recurrent neural network.

    Science.gov (United States)

    Soma, Ken-ichiro; Mori, Ryota; Sato, Ryuichi; Furumai, Noriyuki; Nara, Shigetoshi

    2015-05-01

    We propose neural network model that demonstrates the phenomenon of signal transfer between separated neuron groups via other chaotic neurons that show no apparent correlations with the input signal. The model is a recurrent neural network in which it is supposed that synchronous behavior between small groups of input and output neurons has been learned as fragments of high-dimensional memory patterns, and depletion of neural connections results in chaotic wandering dynamics. Computer experiments show that when a strong oscillatory signal is applied to an input group in the chaotic regime, the signal is successfully transferred to the corresponding output group, although no correlation is observed between the input signal and the intermediary neurons. Signal transfer is also observed when multiple signals are applied simultaneously to separate input groups belonging to different memory attractors. In this sense simultaneous multichannel communications are realized, and the chaotic neural dynamics acts as a signal transfer medium in which the signal appears to be hidden.

  17. A new method of machine vision reprocessing based on cellular neural networks

    International Nuclear Information System (INIS)

    Jianhua, W.; Liping, Z.; Fenfang, Z.; Guojian, H.

    1996-01-01

    This paper proposed a method of image preprocessing in machine vision based on Cellular Neural Network (CNN). CNN is introduced to design image smoothing, image recovering, image boundary detecting and other image preprocessing problems. The proposed methods are so simple that the speed of algorithms are increased greatly to suit the needs of real-time image processing. The experimental results show a satisfactory reply

  18. GPM ground validation via commercial cellular networks: an exploratory approach

    Science.gov (United States)

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Brasjen, Noud; Uijlenhoet, Remko

    2016-04-01

    The suitability of commercial microwave link networks for ground validation of GPM (Global Precipitation Measurement) data is evaluated here. Two state-of-the-art rainfall products are compared over the land surface of the Netherlands for a period of 7 months, i.e., rainfall maps from commercial cellular communication networks and Integrated Multi-satellite Retrievals for GPM (IMERG). Commercial microwave link networks are nowadays the core component in telecommunications worldwide. Rainfall rates can be retrieved from measurements of attenuation between transmitting and receiving antennas. If adequately set up, these networks enable rainfall monitoring tens of meters above the ground at high spatiotemporal resolutions (temporal sampling of seconds to tens of minutes, and spatial sampling of hundreds of meters to tens of kilometers). The GPM mission is the successor of TRMM (Tropical Rainfall Measurement Mission). For two years now, IMERG offers rainfall estimates across the globe (180°W - 180°E and 60°N - 60°S) at spatiotemporal resolutions of 0.1° x 0.1° every 30 min. These two data sets are compared against a Dutch gauge-adjusted radar data set, considered to be the ground truth given its accuracy, spatiotemporal resolution and availability. The suitability of microwave link networks in satellite rainfall evaluation is of special interest, given the independent character of this technique, its high spatiotemporal resolutions and availability. These are valuable assets for water management and modeling of floods, landslides, and weather extremes; especially in places where rain gauge networks are scarce or poorly maintained, or where weather radar networks are too expensive to acquire and/or maintain.

  19. All-optical signal processing for optical packet switching networks

    NARCIS (Netherlands)

    Liu, Y.; Hill, M.T.; Calabretta, N.; Tangdiongga, E.; Geldenhuys, R.; Zhang, S.; Li, Z.; Waardt, de H.; Khoe, G.D.; Dorren, H.J.S.; Iftekharuddin, K.M.; awwal, A.A.S.

    2005-01-01

    We discuss how all-optical signal processing might play a role in future all-optical packet switched networks. We introduce a concept of optical packet switches that employ entirely all-optical signal processing technology. The optical packet switch is made out of three functional blocks: the

  20. Hierarchical random cellular neural networks for system-level brain-like signal processing.

    Science.gov (United States)

    Kozma, Robert; Puljic, Marko

    2013-09-01

    Sensory information processing and cognition in brains are modeled using dynamic systems theory. The brain's dynamic state is described by a trajectory evolving in a high-dimensional state space. We introduce a hierarchy of random cellular automata as the mathematical tools to describe the spatio-temporal dynamics of the cortex. The corresponding brain model is called neuropercolation which has distinct advantages compared to traditional models using differential equations, especially in describing spatio-temporal discontinuities in the form of phase transitions. Phase transitions demarcate singularities in brain operations at critical conditions, which are viewed as hallmarks of higher cognition and awareness experience. The introduced Monte-Carlo simulations obtained by parallel computing point to the importance of computer implementations using very large-scale integration (VLSI) and analog platforms. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. CBL-CIPK network for calcium signaling in higher plants

    Science.gov (United States)

    Luan, Sheng

    Plants sense their environment by signaling mechanisms involving calcium. Calcium signals are encoded by a complex set of parameters and decoded by a large number of proteins including the more recently discovered CBL-CIPK network. The calcium-binding CBL proteins specifi-cally interact with a family of protein kinases CIPKs and regulate the activity and subcellular localization of these kinases, leading to the modification of kinase substrates. This represents a paradigm shift as compared to a calcium signaling mechanism from yeast and animals. One example of CBL-CIPK signaling pathways is the low-potassium response of Arabidopsis roots. When grown in low-K medium, plants develop stronger K-uptake capacity adapting to the low-K condition. Recent studies show that the increased K-uptake is caused by activation of a specific K-channel by the CBL-CIPK network. A working model for this regulatory pathway will be discussed in the context of calcium coding and decoding processes.

  2. EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.

    Directory of Open Access Journals (Sweden)

    Kumari Sonal Choudhary

    2016-06-01

    Full Text Available Epithelial to mesenchymal transition (EMT is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR, are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E and mesenchymal (EGFR_M networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend.

  3. EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.

    Science.gov (United States)

    Choudhary, Kumari Sonal; Rohatgi, Neha; Halldorsson, Skarphedinn; Briem, Eirikur; Gudjonsson, Thorarinn; Gudmundsson, Steinn; Rolfsson, Ottar

    2016-06-01

    Epithelial to mesenchymal transition (EMT) is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR), are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E) and mesenchymal (EGFR_M) networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend.

  4. E3Net: a system for exploring E3-mediated regulatory networks of cellular functions.

    Science.gov (United States)

    Han, Youngwoong; Lee, Hodong; Park, Jong C; Yi, Gwan-Su

    2012-04-01

    Ubiquitin-protein ligase (E3) is a key enzyme targeting specific substrates in diverse cellular processes for ubiquitination and degradation. The existing findings of substrate specificity of E3 are, however, scattered over a number of resources, making it difficult to study them together with an integrative view. Here we present E3Net, a web-based system that provides a comprehensive collection of available E3-substrate specificities and a systematic framework for the analysis of E3-mediated regulatory networks of diverse cellular functions. Currently, E3Net contains 2201 E3s and 4896 substrates in 427 organisms and 1671 E3-substrate specific relations between 493 E3s and 1277 substrates in 42 organisms, extracted mainly from MEDLINE abstracts and UniProt comments with an automatic text mining method and additional manual inspection and partly from high throughput experiment data and public ubiquitination databases. The significant functions and pathways of the extracted E3-specific substrate groups were identified from a functional enrichment analysis with 12 functional category resources for molecular functions, protein families, protein complexes, pathways, cellular processes, cellular localization, and diseases. E3Net includes interactive analysis and navigation tools that make it possible to build an integrative view of E3-substrate networks and their correlated functions with graphical illustrations and summarized descriptions. As a result, E3Net provides a comprehensive resource of E3s, substrates, and their functional implications summarized from the regulatory network structures of E3-specific substrate groups and their correlated functions. This resource will facilitate further in-depth investigation of ubiquitination-dependent regulatory mechanisms. E3Net is freely available online at http://pnet.kaist.ac.kr/e3net.

  5. Mitochondrial correlates of signaling processes involved with the cellular response to eimeria infection in broiler chickens

    Science.gov (United States)

    Host cellular responses to coccidiosis infection are consistent with elements of apoptosis, autophagy, and necrosis. These processes are enhanced in the cell through cell-directed signaling or repressed through parasite-derived inhibitors of these processes favoring the survival of the parasite. Acr...

  6. Pathloss Measurements and Modeling for UAVs Connected to Cellular Networks

    DEFF Research Database (Denmark)

    Amorim, Rafhael Medeiros de; Mogensen, Preben Elgaard; Sørensen, Troels Bundgaard

    2017-01-01

    . The measurements were conducted in an operating LTE network (850 MHz), using a commercial cell phone, placed inside the frame of the UAV. Trials were conducted for UAV flying at 5 different heights measured above ground level (20, 40, 60, 80 and 100m) and a pathloss regression line was obtained from results. Then......This paper assess field measurements, as part of the investigation of the suitability of cellular networks for providing connectivity to UAVs (unmanned aerial vehicles). Evaluation is done by means of field measurements obtained in a rural environment in Denmark with an airbone UAV......, downlink (DL) SINR levels obtained during flight measurements are also presented. An important result obtained from the measurents reveal that there is a height-related DL SINR degradation. Three main sources of uncertainty on the pathloss model that could be responsible for the SINR degradation are also...

  7. Urban Traffic Signal System Control Structural Optimization Based on Network Analysis

    Directory of Open Access Journals (Sweden)

    Li Wang

    2013-01-01

    Full Text Available Advanced urban traffic signal control systems such as SCOOT and SCATS normally coordinate traffic network using multilevel hierarchical control mechanism. In this mechanism, several key intersections will be selected from traffic signal network and the network will be divided into different control subareas. Traditionally, key intersection selection and control subareas division are executed according to dynamic traffic counts and link length between intersections, which largely rely on traffic engineers’ experience. However, it omits important inherent characteristics of traffic network topology. In this paper, we will apply network analysis approach into these two aspects for traffic system control structure optimization. Firstly, the modified C-means clustering algorithm will be proposed to assess the importance of intersections in traffic network and furthermore determine the key intersections based on three indexes instead of merely on traffic counts in traditional methods. Secondly, the improved network community discovery method will be used to give more reasonable evidence in traffic control subarea division. Finally, to test the effectiveness of network analysis approach, a hardware-in-loop simulation environment composed of regional traffic control system, microsimulation software and signal controller hardware, will be built. Both traditional method and proposed approach will be implemented on simulation test bed to evaluate traffic operation performance indexes, for example, travel time, stop times, delay and average vehicle speed. Simulation results show that the proposed network analysis approach can improve the traffic control system operation performance effectively.

  8. Robust Nash Dynamic Game Strategy for User Cooperation Energy Efficiency in Wireless Cellular Networks

    Directory of Open Access Journals (Sweden)

    Shuhuan Wen

    2012-01-01

    Full Text Available Recently, there is an emerging trend of addressing “energy efficiency” aspect of wireless communications. It has been shown that cooperating users relay each other's information to improve data rates. The energy is limited in the wireless cellular network, but the mobile users refuse to relay. This paper presents an approach that encourages user cooperation in order to improve the energy efficiency. The game theory is an efficient method to solve such conflicts. We present a cellular framework in which two mobile users, who desire to communicate with a common base station, may cooperate via decode-and-forward relaying. In the case of imperfect information assumption, cooperative Nash dynamic game is used between the two users' cooperation to tackle the decision making problems: whether to cooperate and how to cooperate in wireless networks. The scheme based on “cooperative game theory” can achieve general pareto-optimal performance for cooperative games, and thus, maximize the entire system payoff while maintaining fairness.

  9. 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.

  10. Neural network committees for finger joint angle estimation from surface EMG signals

    Directory of Open Access Journals (Sweden)

    Reddy Narender P

    2009-01-01

    Full Text Available Abstract Background In virtual reality (VR systems, the user's finger and hand positions are sensed and used to control the virtual environments. Direct biocontrol of VR environments using surface electromyography (SEMG signals may be more synergistic and unconstraining to the user. The purpose of the present investigation was to develop a technique to predict the finger joint angle from the surface EMG measurements of the extensor muscle using neural network models. Methodology SEMG together with the actual joint angle measurements were obtained while the subject was performing flexion-extension rotation of the index finger at three speeds. Several neural networks were trained to predict the joint angle from the parameters extracted from the SEMG signals. The best networks were selected to form six committees. The neural network committees were evaluated using data from new subjects. Results There was hysteresis in the measured SMEG signals during the flexion-extension cycle. However, neural network committees were able to predict the joint angle with reasonable accuracy. RMS errors ranged from 0.085 ± 0.036 for fast speed finger-extension to 0.147 ± 0.026 for slow speed finger extension, and from 0.098 ± 0.023 for the fast speed finger flexion to 0.163 ± 0.054 for slow speed finger flexion. Conclusion Although hysteresis was observed in the measured SEMG signals, the committees of neural networks were able to predict the finger joint angle from SEMG signals.

  11. The pathogen-actin connection: A platform for defense signaling in plants

    Energy Technology Data Exchange (ETDEWEB)

    Day, B; Henty, Jessica L; Porter, K J; Staiger, Chris J

    2011-09-08

    The cytoskeleton, a dynamic network of cytoplasmic polymers, plays a central role in numerous fundamental processes, such as development, reproduction, and cellular responses to biotic and abiotic stimuli. As a platform for innate immune responses in mammalian cells, the actin cytoskeleton is a central component in the organization and activation of host defenses, including signaling and cellular repair. In plants, our understanding of the genetic and biochemical responses in both pathogen and host that are required for virulence and resistance has grown enormously. Additional advances in live-cell imaging of cytoskeletal dynamics have markedly altered our view of actin turnover in plants. In this review, we outline current knowledge of host resistance following pathogen perception, both in terms of the genetic interactions that mediate defense signaling, as well as the biochemical and cellular processes that are required for defense signaling.

  12. Cellular signalling properties in microcircuits

    DEFF Research Database (Denmark)

    Toledo-Rodriguez, Maria; El Manira, Abdeljabbar; Wallén, Peter

    2005-01-01

    Molecules and cells are the signalling elements in microcircuits. Recent studies have uncovered bewildering diversity in postsynaptic signalling properties in all areas of the vertebrate nervous system. Major effort is now being invested in establishing the specialized signalling properties...

  13. P-Finder: Reconstruction of Signaling Networks from Protein-Protein Interactions and GO Annotations.

    Science.gov (United States)

    Young-Rae Cho; Yanan Xin; Speegle, Greg

    2015-01-01

    Because most complex genetic diseases are caused by defects of cell signaling, illuminating a signaling cascade is essential for understanding their mechanisms. We present three novel computational algorithms to reconstruct signaling networks between a starting protein and an ending protein using genome-wide protein-protein interaction (PPI) networks and gene ontology (GO) annotation data. A signaling network is represented as a directed acyclic graph in a merged form of multiple linear pathways. An advanced semantic similarity metric is applied for weighting PPIs as the preprocessing of all three methods. The first algorithm repeatedly extends the list of nodes based on path frequency towards an ending protein. The second algorithm repeatedly appends edges based on the occurrence of network motifs which indicate the link patterns more frequently appearing in a PPI network than in a random graph. The last algorithm uses the information propagation technique which iteratively updates edge orientations based on the path strength and merges the selected directed edges. Our experimental results demonstrate that the proposed algorithms achieve higher accuracy than previous methods when they are tested on well-studied pathways of S. cerevisiae. Furthermore, we introduce an interactive web application tool, called P-Finder, to visualize reconstructed signaling networks.

  14. The Effect of Spatial Interference Correlation and Jamming on Secrecy in Cellular Networks

    KAUST Repository

    Ali, Konpal S.

    2017-06-02

    Recent studies on secure wireless communication have shed light on a scenario where interference has a desirable impact on network performance. Particularly, assuming independent interference-power fluctuations at the eavesdropper and the receiver, opportunistic secure-information transfer can occur on the legitimate-link. However, interference is spatially correlated due to the common set of interfering sources, which may diminish the opportunistic-secure-spectrum-access (OSSA) probability. We study and quantify the effect of spatial interference correlation on OSSA in cellular-networks and investigate the potential of full-duplex jamming (FDJ) solutions. The results highlight the scenarios where FDJ improves OSSA performance.

  15. The Effect of Spatial Interference Correlation and Jamming on Secrecy in Cellular Networks

    KAUST Repository

    Ali, Konpal S.; Elsawy, Hesham; Haenggi, Martin; Alouini, Mohamed-Slim

    2017-01-01

    Recent studies on secure wireless communication have shed light on a scenario where interference has a desirable impact on network performance. Particularly, assuming independent interference-power fluctuations at the eavesdropper and the receiver, opportunistic secure-information transfer can occur on the legitimate-link. However, interference is spatially correlated due to the common set of interfering sources, which may diminish the opportunistic-secure-spectrum-access (OSSA) probability. We study and quantify the effect of spatial interference correlation on OSSA in cellular-networks and investigate the potential of full-duplex jamming (FDJ) solutions. The results highlight the scenarios where FDJ improves OSSA performance.

  16. Global stability and existence of periodic solutions of discrete delayed cellular neural networks

    International Nuclear Information System (INIS)

    Li Yongkun

    2004-01-01

    We use the continuation theorem of coincidence degree theory and Lyapunov functions to study the existence and stability of periodic solutions for the discrete cellular neural networks (CNNs) with delays xi(n+1)=xi(n)e-bi(n)h+θi(h)-bar j=1maij(n)fj(xj(n))+θi(h)-bar j=1mbij(n)fj(xj(n- τij(n)))+θi(h)Ii(n),i=1,2,...,m. We obtain some sufficient conditions to ensure that for the networks there exists a unique periodic solution, and all its solutions converge to such a periodic solution

  17. Cellular Neural Networks for NP-Hard Optimization

    Directory of Open Access Journals (Sweden)

    Mária Ercsey-Ravasz

    2009-02-01

    Full Text Available A cellular neural/nonlinear network (CNN is used for NP-hard optimization. We prove that a CNN in which the parameters of all cells can be separately controlled is the analog correspondent of a two-dimensional Ising-type (Edwards-Anderson spin-glass system. Using the properties of CNN, we show that one single operation (template always yields a local minimum of the spin-glass energy function. This way, a very fast optimization method, similar to simulated annealing, can be built. Estimating the simulation time needed on CNN-based computers, and comparing it with the time needed on normal digital computers using the simulated annealing algorithm, the results are astonishing. CNN computers could be faster than digital computers already at 10×10 lattice sizes. The local control of the template parameters was already partially realized on some of the hardwares, we think this study could further motivate their development in this direction.

  18. Uplink Interference Analysis for Two-tier Cellular Networks with Diverse Users under Random Spatial Patterns

    OpenAIRE

    Bao, Wei; Liang, Ben

    2013-01-01

    Multi-tier architecture improves the spatial reuse of radio spectrum in cellular networks, but it introduces complicated heterogeneity in the spatial distribution of transmitters, which brings new challenges in interference analysis. In this work, we present a stochastic geometric model to evaluate the uplink interference in a two-tier network considering multi-type users and base stations. Each type of tier-1 users and tier-2 base stations are modeled as independent homogeneous Poisson point...

  19. Efficient Radio Resource Allocation in a GSM and GPRS Cellular Network

    Directory of Open Access Journals (Sweden)

    David Vannucci

    2004-10-01

    Full Text Available This paper investigates the effect of various radio resource allocation strategies in a GSM/GPRS cellular network. The most efficient resource allocation is analysed as a function of the proportion of circuit switched voice and packet switched data load. The Grade of Service and average packet delay is investigated as a function of the load, packet size and call duration. Additionally, the feasibility of using voice over Internet Protocol as opposed to circuit switched voice is investigated as a means to increase subscriber capacity per base station. The work is motivated firstly by the complexity of having both circuit switched and packet switched connectivity on GSM/GPRS mobile cellular system and secondly that an exclusively packet based access on GSM/GPRS has the potential to increase the efficiency of resource utilisation by suitably varying the channel allocation to exploit the characteristics of voice and data traffic.

  20. Downlink Performance of a Multi-Carrier MIMO System in a Bursty Traffic Cellular Network

    DEFF Research Database (Denmark)

    Nguyen, Hung Tuan; Kovacs, Istvan; Wang, Yuanye

    2011-01-01

    In this paper we analyse the downlink performance of a rank adaptive multiple input multiple output (MIMO) system in a busty traffic cellular network. A LTE-Advanced system with multiple component carriers was selected as a study case. To highlight the advantage of using MIMO techniques, we used ...

  1. Perturbation of cellular signaling cascades modulated by ionizing radiation and environmental stress

    International Nuclear Information System (INIS)

    Ugolini, M.

    2014-01-01

    Cellular signaling plays a central role in the regulation of several cell functions, which can be perturbed by different external stimuli, including environmental stress and ionizing radiation. The dysregulation of intra- and extracellular mechanisms may alter the correct behaviour of cells. The aim of this work was to investigate the activation of strongly interlaced intracellular signaling pathways, following the exposure to low- and medium-doses of X-rays, with a focus on the mechanisms involved in the inflammatory- and apoptotic-related responses. In particular, the temporal dynamics of the ERK1/2 and PKB/AKT pathways and their possible dose dependences were investigated. The presented results indicate a clear dose dependence of such pathways only at early time points, suggesting a fast response of the system to X-rays and the need for further studies at shorter times after exposures.

  2. Optimal Signal Design for Mixed Equilibrium Networks with Autonomous and Regular Vehicles

    Directory of Open Access Journals (Sweden)

    Nan Jiang

    2017-01-01

    Full Text Available A signal design problem is studied for efficiently managing autonomous vehicles (AVs and regular vehicles (RVs simultaneously in transportation networks. AVs and RVs move on separate lanes and two types of vehicles share the green times at the same intersections. The signal design problem is formulated as a bilevel program. The lower-level model describes a mixed equilibrium where autonomous vehicles follow the Cournot-Nash (CN principle and RVs follow the user equilibrium (UE principle. In the upper-level model, signal timings are optimized at signalized intersections to allocate appropriate green times to both autonomous and RVs to minimize system travel cost. The sensitivity analysis based method is used to solve the bilevel optimization model. Various signal control strategies are evaluated through numerical examples and some insightful findings are obtained. It was found that the number of phases at intersections should be reduced for the optimal control of the AVs and RVs in the mixed networks. More importantly, incorporating AVs into the transportation network would improve the system performance due to the value of AV technologies in reducing random delays at intersections. Meanwhile, travelers prefer to choose AVs when the networks turn to be congested.

  3. Plant morphogenesis, auxin, and the signal-trafficking network incompleteness theorem

    Directory of Open Access Journals (Sweden)

    Karl J. Niklas

    2012-03-01

    Full Text Available Plant morphogenesis (the development of form and function requires signal-trafficking and cross-talking among all levels of organization to coordinate the operation of metabolic and genomic networked systems. Many if not all of these biological features can be rendered as logic circuits supervising the operation of one or more signal-activated metabolic or genome networks. This approach simplifies complex morphogenetic phenomena and allows for their aggregation into diagrams of larger, more "global" networked systems. This conceptualization is illustrated for morphogenesis in model plants such as maize (Zea mays and Thale cress (Arabidopsis thaliana from an evolutionary perspective. The phytohormone indole-acetic acid (IAA is used as an example for a well-known signaling chemical and discussed in terms of the logic circuits and signal-activated sub-systems for hormone-mediated wall loosening and cell expansion as well as polar/lateral intercellular IAA transport. For each of these phenomena, a circuit/sub-system diagram highlights missing components, either in the logic circuit or in the sub-system it supervises, that must be identified experimentally if each of these basic phenomena is to be fully understood within a phylogen

  4. Fisetin and hesperetin induced apoptosis and cell cycle arrest in chronic myeloid leukemia cells accompanied by modulation of cellular signaling.

    Science.gov (United States)

    Adan, Aysun; Baran, Yusuf

    2016-05-01

    Fisetin and hesperetin, naturally occurring flavonoids, have been reported as novel antioxidants with chemopreventive/chemotherapeutic potential against various types of cancer. However, their mechanism of action in CML is still unknown. This particular study aims to evaluate the therapeutic potentials of fisetin and hesperetin and their effects on cell proliferation, apoptosis, and cell cycle progression in human K562 CML cells. The results indicated that fisetin and hesperetin inhibited cell proliferation and triggered programmed cell death in these cells. The latter was confırmed by mitochondrial membrane depolarization and an increase in caspase-3 activation. In addition to that, we have detected S and G2/M cell cycle arrests and G0/G1 arrest upon fisetin and hesperetin treatment, respectively. To identify the altered genes and genetic networks in response to fisetin and hesperetin, whole-genome microarray analysis was performed. The microarray gene profiling analysis revealed some important signaling pathways including JAK/STAT pathway, KIT receptor signaling, and growth hormone receptor signaling that were altered upon fisetin and hesperetin treatment. Moreover, microarray data suggested potential candidate genes for targeted CML therapy. Fisetin and hesperetin significantly modulated the expression of genes involved in cell proliferation and division, apoptosis, cell cycle regulation, and other significant cellular processes such as replication, transcription, and translation. In conclusion, our results suggest that fisetin and hesperetin as potential natural agents for CML therapy.

  5. Signal Processing Device (SPD) for networked radiation monitoring system

    International Nuclear Information System (INIS)

    Dharmapurikar, A.; Bhattacharya, S.; Mukhopadhyay, P.K.; Sawhney, A.; Patil, R.K.

    2010-01-01

    A networked radiation and parameter monitoring system with three tier architecture is being developed. Signal Processing Device (SPD) is a second level sub-system node in the network. SPD is an embedded system which has multiple input channels and output communication interfaces. It acquires and processes data from first level parametric sensor devices, and sends to third level devices in response to request commands received from host. It also performs scheduled diagnostic operations and passes on the information to host. It supports inputs in the form of differential digital signals and analog voltage signals. SPD communicates with higher level devices over RS232/RS422/USB channels. The system has been designed with main requirements of minimal power consumption and harsh environment in radioactive plants. This paper discusses the hardware and software design details of SPD. (author)

  6. Research on the Wire Network Signal Prediction Based on the Improved NNARX Model

    Science.gov (United States)

    Zhang, Zipeng; Fan, Tao; Wang, Shuqing

    It is difficult to obtain accurately the wire net signal of power system's high voltage power transmission lines in the process of monitoring and repairing. In order to solve this problem, the signal measured in remote substation or laboratory is employed to make multipoint prediction to gain the needed data. But, the obtained power grid frequency signal is delay. In order to solve the problem, an improved NNARX network which can predict frequency signal based on multi-point data collected by remote substation PMU is describes in this paper. As the error curved surface of the NNARX network is more complicated, this paper uses L-M algorithm to train the network. The result of the simulation shows that the NNARX network has preferable predication performance which provides accurate real time data for field testing and maintenance.

  7. Traffic signal synchronization in the saturated high-density grid road network.

    Science.gov (United States)

    Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

    2015-01-01

    Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

  8. Cognitive Radio and its Application for Next Generation Cellular and Wireless Networks

    CERN Document Server

    Muntean, Gabriel-Miro

    2012-01-01

    This book provides a broad introduction to Cognitive Radio, which attempts to mimic human cognition and reasoning applied to Software Defined Radio and reconfigurable radio over wireless networks.  It provides readers with significant technical and practical insights into different aspects of Cognitive Radio, starting from a basic background, the principle behind the technology, the inter-related technologies and application to cellular and vehicular networks, the technical challenges, implementation and future trends.  The discussion balances theoretical concepts and practical implementation. Wherever feasible, the different concepts explained are linked to application of the corresponding scheme in a particular wireless standard.     This book has two sections: the first section begins with an introduction to cognitive radio and discusses in detail various, inter-dependent technologies such as network coding, software-based radio, dirty RF, etc. and their relation to cognitive radio. The second section ...

  9. Transduction motif analysis of gastric cancer based on a human signaling network

    Energy Technology Data Exchange (ETDEWEB)

    Liu, G.; Li, D.Z.; Jiang, C.S.; Wang, W. [Fuzhou General Hospital of Nanjing Command, Department of Gastroenterology, Fuzhou, China, Department of Gastroenterology, Fuzhou General Hospital of Nanjing Command, Fuzhou (China)

    2014-04-04

    To investigate signal regulation models of gastric cancer, databases and literature were used to construct the signaling network in humans. Topological characteristics of the network were analyzed by CytoScape. After marking gastric cancer-related genes extracted from the CancerResource, GeneRIF, and COSMIC databases, the FANMOD software was used for the mining of gastric cancer-related motifs in a network with three vertices. The significant motif difference method was adopted to identify significantly different motifs in the normal and cancer states. Finally, we conducted a series of analyses of the significantly different motifs, including gene ontology, function annotation of genes, and model classification. A human signaling network was constructed, with 1643 nodes and 5089 regulating interactions. The network was configured to have the characteristics of other biological networks. There were 57,942 motifs marked with gastric cancer-related genes out of a total of 69,492 motifs, and 264 motifs were selected as significantly different motifs by calculating the significant motif difference (SMD) scores. Genes in significantly different motifs were mainly enriched in functions associated with cancer genesis, such as regulation of cell death, amino acid phosphorylation of proteins, and intracellular signaling cascades. The top five significantly different motifs were mainly cascade and positive feedback types. Almost all genes in the five motifs were cancer related, including EPOR, MAPK14, BCL2L1, KRT18, PTPN6, CASP3, TGFBR2, AR, and CASP7. The development of cancer might be curbed by inhibiting signal transductions upstream and downstream of the selected motifs.

  10. New results of almost periodic solutions for cellular neural networks with mixed delays

    International Nuclear Information System (INIS)

    Zhao Weirui; Zhang Huanshui

    2009-01-01

    In this paper, for cellular neural networks with mixed delays, we prove some new results on the existence of almost periodic solutions by contraction principle. The global exponential stability of almost periodic solutions is discussed further, and conditions for exponential convergence are given. The conditions we obtained are weaker than the previously known ones and can be easily reduced to several special cases.

  11. NT2 derived neuronal and astrocytic network signalling.

    Directory of Open Access Journals (Sweden)

    Eric J Hill

    Full Text Available A major focus of stem cell research is the generation of neurons that may then be implanted to treat neurodegenerative diseases. However, a picture is emerging where astrocytes are partners to neurons in sustaining and modulating brain function. We therefore investigated the functional properties of NT2 derived astrocytes and neurons using electrophysiological and calcium imaging approaches. NT2 neurons (NT2Ns expressed sodium dependent action potentials, as well as responses to depolarisation and the neurotransmitter glutamate. NT2Ns exhibited spontaneous and coordinated calcium elevations in clusters and in extended processes, indicating local and long distance signalling. Tetrodotoxin sensitive network activity could also be evoked by electrical stimulation. Similarly, NT2 astrocytes (NT2As exhibited morphology and functional properties consistent with this glial cell type. NT2As responded to neuronal activity and to exogenously applied neurotransmitters with calcium elevations, and in contrast to neurons, also exhibited spontaneous rhythmic calcium oscillations. NT2As also generated propagating calcium waves that were gap junction and purinergic signalling dependent. Our results show that NT2 derived astrocytes exhibit appropriate functionality and that NT2N networks interact with NT2A networks in co-culture. These findings underline the utility of such cultures to investigate human brain cell type signalling under controlled conditions. Furthermore, since stem cell derived neuron function and survival is of great importance therapeutically, our findings suggest that the presence of complementary astrocytes may be valuable in supporting stem cell derived neuronal networks. Indeed, this also supports the intriguing possibility of selective therapeutic replacement of astrocytes in diseases where these cells are either lost or lose functionality.

  12. [A wavelet neural network algorithm of EEG signals data compression and spikes recognition].

    Science.gov (United States)

    Zhang, Y; Liu, A; Yu, K

    1999-06-01

    A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented. The wavelet network not only can compress data effectively but also can recover original signal. In addition, the characters of the spikes and the spike-slow rhythm are auto-detected from the time-frequency isoline of EEG signal. This method is well worth using in the field of the electrophysiological signal processing and time-frequency analyzing.

  13. Three-dimensional WS2 nanosheet networks for H2O2 produced for cell signaling

    Science.gov (United States)

    Tang, Jing; Quan, Yingzhou; Zhang, Yueyu; Jiang, Min; Al-Enizi, Abdullah M.; Kong, Biao; An, Tiance; Wang, Wenshuo; Xia, Limin; Gong, Xingao; Zheng, Gengfeng

    2016-03-01

    Hydrogen peroxide (H2O2) is an important molecular messenger for cellular signal transduction. The capability of direct probing of H2O2 in complex biological systems can offer potential for elucidating its manifold roles in living systems. Here we report the fabrication of three-dimensional (3D) WS2 nanosheet networks with flower-like morphologies on a variety of conducting substrates. The semiconducting WS2 nanosheets with largely exposed edge sites on flexible carbon fibers enable abundant catalytically active sites, excellent charge transfer, and high permeability to chemicals and biomaterials. Thus, the 3D WS2-based nano-bio-interface exhibits a wide detection range, high sensitivity and rapid response time for H2O2, and is capable of visualizing endogenous H2O2 produced in living RAW 264.7 macrophage cells and neurons. First-principles calculations further demonstrate that the enhanced sensitivity of probing H2O2 is attributed to the efficient and spontaneous H2O2 adsorption on WS2 nanosheet edge sites. The combined features of 3D WS2 nanosheet networks suggest attractive new opportunities for exploring the physiological roles of reactive oxygen species like H2O2 in living systems.Hydrogen peroxide (H2O2) is an important molecular messenger for cellular signal transduction. The capability of direct probing of H2O2 in complex biological systems can offer potential for elucidating its manifold roles in living systems. Here we report the fabrication of three-dimensional (3D) WS2 nanosheet networks with flower-like morphologies on a variety of conducting substrates. The semiconducting WS2 nanosheets with largely exposed edge sites on flexible carbon fibers enable abundant catalytically active sites, excellent charge transfer, and high permeability to chemicals and biomaterials. Thus, the 3D WS2-based nano-bio-interface exhibits a wide detection range, high sensitivity and rapid response time for H2O2, and is capable of visualizing endogenous H2O2 produced in

  14. Determination of outdoor signal propagation via visibility analysis in outdoor wireless networks

    Directory of Open Access Journals (Sweden)

    Mustafa Coşar

    2017-02-01

    Full Text Available Wireless networks on university campuses has gained importance in recent years. These networks in major areas such as university campuses, are faced with many problems during the planning, design and establishment. These problems are among the first that comes to mind, the physical properties of the campus and is selected according to the characteristics of network equipment. There is no doubt at all points of a wireless network set up in order to provide uninterrupted service and quality of the signal is expected to be good. However, it should be understood literally cannot meet these expectations. Therefore, to solve many problems to campus planning and design can be made to have acceptable signal distribution will have the appropriate use of and satisfaction with increasing effect. In this study, due to the start of construction on the North Campus of Hitit University, wireless signal spread using the current spread has been determined with the help of geographic information systems visibility analysis. An area of 56 hectares, with the total of 9 AP the acceptable signal distribution was obtained.

  15. Early leaf senescence is associated with an altered cellular redox balance in Arabidopsis cpr5/old1 mutants

    OpenAIRE

    Jing, H. -C.; Hebeler, R.; Oeljeklaus, S.; Sitek, B.; Stuehler, K.; Meyer, H. E.; Sturre, M. J. G.; Hille, J.; Warscheid, B.; Dijkwel, P. P.; Stühler, K.

    2008-01-01

    Reactive oxygen species (ROS) are the inevitable by-products of essential cellular metabolic and physiological activities. Plants have developed sophisticated gene networks of ROS generation and scavenging systems. However, ROS regulation is still poorly understood. Here, we report that mutations in the Arabidopsis CPR5/OLD1 gene may cause early senescence through deregulation of the cellular redox balance. Genetic analysis showed that blocking stress-related hormonal signalling pathways, suc...

  16. A game theoretical approach for cooperative environmentally friendly cellular networks powered by the smart grid

    KAUST Repository

    Ghazzai, Hakim

    2014-11-01

    This paper investigates the collaboration between multiple mobile operators to optimize the energy efficiency of cellular networks, maximize their profits or achieve or tradeoff between both objectives. Mobile operators cooperate together by eliminating redundant base stations (BSs) using a low complexity algorithm that aims to maximize their objective functions subject to a quality of service constraint. The problem is modeled as a two-level Stackelberg game: a mobile operator level and a smart grid level. Indeed, in our framework, we assume that cellular networks are powered by multiple energy providers existing in the smart grid characterized by different pollutant levels in addition to renewable energy source deployed in BS sites. The objective is to find the best active BS combination and the optimal procurement decision needed to the network operation during collaboration by considering electricity real-time pricing. Our study includes the daily traffic variation in addition to the daily green energy availability. Our simulation results show a significant saving in terms of CO2 emissions compared to the non-collaboration case and that cooperative mobile operators exploiting renewables are more awarded than traditional operators. © 2014 IEEE.

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

    Science.gov (United States)

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

    2015-01-01

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

  18. Measuring urban rainfall using microwave links from commercial cellular communication networks

    NARCIS (Netherlands)

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2011-01-01

    The estimation of rainfall using commercial microwave links is a new and promising measurement technique. Commercial link networks cover large parts of the land surface of the earth and have a high density, particularly in urban areas. Rainfall attenuates the electromagnetic signals transmitted

  19. A Hybrid Energy Sharing Framework for Green Cellular Networks

    KAUST Repository

    Farooq, Muhammad Junaid

    2016-12-09

    Cellular operators are increasingly turning towards renewable energy (RE) as an alternative to using traditional electricity in order to reduce operational expenditure and carbon footprint. Due to the randomness in both RE generation and mobile traffic at each base station (BS), a surplus or shortfall of energy may occur at any given time. To increase energy selfreliance and minimize the network’s energy cost, the operator needs to efficiently exploit the RE generated across all BSs. In this paper, a hybrid energy sharing framework for cellular network is proposed, where a combination of physical power lines and energy trading with other BSs using smart grid is used. Algorithms for physical power lines deployment between BSs, based on average and complete statistics of the net RE available, are developed. Afterwards, an energy management framework is formulated to optimally determine the quantities of electricity and RE to be procured and exchanged among BSs, respectively, while considering battery capacities and real-time energy pricing. Three cases are investigated where RE generation is unknown, perfectly known, and partially known ahead of time. Results investigate the time varying energy management of BSs and demonstrate considerable reduction in average energy cost thanks to the hybrid energy sharing scheme.

  20. Protease-associated cellular networks in malaria parasite Plasmodium falciparum

    Directory of Open Access Journals (Sweden)

    Lilburn Timothy G

    2011-12-01

    Full Text Available Abstract Background Malaria continues to be one of the most severe global infectious diseases, responsible for 1-2 million deaths yearly. The rapid evolution and spread of drug resistance in parasites has led to an urgent need for the development of novel antimalarial targets. Proteases are a group of enzymes that play essential roles in parasite growth and invasion. The possibility of designing specific inhibitors for proteases makes them promising drug targets. Previously, combining a comparative genomics approach and a machine learning approach, we identified the complement of proteases (degradome in the malaria parasite Plasmodium falciparum and its sibling species 123, providing a catalog of targets for functional characterization and rational inhibitor design. Network analysis represents another route to revealing the role of proteins in the biology of parasites and we use this approach here to expand our understanding of the systems involving the proteases of P. falciparum. Results We investigated the roles of proteases in the parasite life cycle by constructing a network using protein-protein association data from the STRING database 4, and analyzing these data, in conjunction with the data from protein-protein interaction assays using the yeast 2-hybrid (Y2H system 5, blood stage microarray experiments 678, proteomics 9101112, literature text mining, and sequence homology analysis. Seventy-seven (77 out of 124 predicted proteases were associated with at least one other protein, constituting 2,431 protein-protein interactions (PPIs. These proteases appear to play diverse roles in metabolism, cell cycle regulation, invasion and infection. Their degrees of connectivity (i.e., connections to other proteins, range from one to 143. The largest protease-associated sub-network is the ubiquitin-proteasome system which is crucial for protein recycling and stress response. Proteases are also implicated in heat shock response, signal peptide

  1. Human Age Recognition by Electrocardiogram Signal Based on Artificial Neural Network

    Science.gov (United States)

    Dasgupta, Hirak

    2016-12-01

    The objective of this work is to make a neural network function approximation model to detect human age from the electrocardiogram (ECG) signal. The input vectors of the neural network are the Katz fractal dimension of the ECG signal, frequencies in the QRS complex, male or female (represented by numeric constant) and the average of successive R-R peak distance of a particular ECG signal. The QRS complex has been detected by short time Fourier transform algorithm. The successive R peak has been detected by, first cutting the signal into periods by auto-correlation method and then finding the absolute of the highest point in each period. The neural network used in this problem consists of two layers, with Sigmoid neuron in the input and linear neuron in the output layer. The result shows the mean of errors as -0.49, 1.03, 0.79 years and the standard deviation of errors as 1.81, 1.77, 2.70 years during training, cross validation and testing with unknown data sets, respectively.

  2. The Digital Age of Mobile Cellular Network in Germany and China :Policies, Technologies and Markets (PartⅠ)

    Institute of Scientific and Technical Information of China (English)

    Mingtao Shi

    2009-01-01

    The German Postal Reform Ⅰ in 1989 introduced competition in the mobile cellular market. German cellular operators, DeTeMobil, Mannesmann, E-Plus and VIAG Interkom, built DI-, D2-, El- and E2-Netze based on GSM standards made in Europe. China Unicom was created in 1994 and China Telecom was separated from MPT in 1995. China Telecom and China Unicorn competed in a duopoly from the mid-1990s onwards and the cellular services provided by them also rely on GSM standards. China Telecom additionally deployed XLT technology (PHS) from the late 1990s onwards. While DeTeMobil and Mannesmarm conquered approximately 80%-90% of the market throughout the 1990s and were the two dominant market players in Germany, China's cellular market was mainly controlled by China Mobile. In Germany, prices related to cellular technology continued the downwards trend as a major result of the process of deregulation, liberalisation and competition. In China, price wars bad led to significant price reductions in the cellular market. Although network operators in both countries strived to deliver differentiated cellular Services, the two national markets in the 1990s were visibly shaped by product homogeneity.

  3. Organization of physical interactomes as uncovered by network schemas.

    Science.gov (United States)

    Banks, Eric; Nabieva, Elena; Chazelle, Bernard; Singh, Mona

    2008-10-01

    Large-scale protein-protein interaction networks provide new opportunities for understanding cellular organization and functioning. We introduce network schemas to elucidate shared mechanisms within interactomes. Network schemas specify descriptions of proteins and the topology of interactions among them. We develop algorithms for systematically uncovering recurring, over-represented schemas in physical interaction networks. We apply our methods to the S. cerevisiae interactome, focusing on schemas consisting of proteins described via sequence motifs and molecular function annotations and interacting with one another in one of four basic network topologies. We identify hundreds of recurring and over-represented network schemas of various complexity, and demonstrate via graph-theoretic representations how more complex schemas are organized in terms of their lower-order constituents. The uncovered schemas span a wide range of cellular activities, with many signaling and transport related higher-order schemas. We establish the functional importance of the schemas by showing that they correspond to functionally cohesive sets of proteins, are enriched in the frequency with which they have instances in the H. sapiens interactome, and are useful for predicting protein function. Our findings suggest that network schemas are a powerful paradigm for organizing, interrogating, and annotating cellular networks.

  4. Regulation of Cellular Redox Signaling by Matricellular Proteins in Vascular Biology, Immunology, and Cancer.

    Science.gov (United States)

    Roberts, David D; Kaur, Sukhbir; Isenberg, Jeffrey S

    2017-10-20

    In contrast to structural elements of the extracellular matrix, matricellular proteins appear transiently during development and injury responses, but their sustained expression can contribute to chronic disease. Through interactions with other matrix components and specific cell surface receptors, matricellular proteins regulate multiple signaling pathways, including those mediated by reactive oxygen and nitrogen species and H 2 S. Dysregulation of matricellular proteins contributes to the pathogenesis of vascular diseases and cancer. Defining the molecular mechanisms and receptors involved is revealing new therapeutic opportunities. Recent Advances: Thrombospondin-1 (TSP1) regulates NO, H 2 S, and superoxide production and signaling in several cell types. The TSP1 receptor CD47 plays a central role in inhibition of NO signaling, but other TSP1 receptors also modulate redox signaling. The matricellular protein CCN1 engages some of the same receptors to regulate redox signaling, and ADAMTS1 regulates NO signaling in Marfan syndrome. In addition to mediating matricellular protein signaling, redox signaling is emerging as an important pathway that controls the expression of several matricellular proteins. Redox signaling remains unexplored for many matricellular proteins. Their interactions with multiple cellular receptors remains an obstacle to defining signaling mechanisms, but improved transgenic models could overcome this barrier. Therapeutics targeting the TSP1 receptor CD47 may have beneficial effects for treating cardiovascular disease and cancer and have recently entered clinical trials. Biomarkers are needed to assess their effects on redox signaling in patients and to evaluate how these contribute to their therapeutic efficacy and potential side effects. Antioxid. Redox Signal. 27, 874-911.

  5. Green collaboration in cognitive radio cellular networks with roaming and spectrum trading

    KAUST Repository

    Sboui, Lokman

    2015-08-30

    In this paper, we propose a new cognitive cellular network architecture based on the coexistence of primary and secondary networks, (PN) and (SN), respectively. The PN aims to minimize its energy consumption by switching off the maximum number of its BSs and offloading its users to the SN\\'s infrastructure to maintain its QoS. In return, the PN pays a roaming price and permits the SN to share or lease the spectrum at a certain price. We propose a low-complexity algorithm allowing the PN to minimize its energy consumption by selecting a suboptimal combination of active base stations. Our algorithm also optimizes the resource allocation of the SN to maximize its total sum-rate while respecting the minimal profit constraints for both networks. In the numerical results, we show that our proposed algorithm achieves close performances to the optimal exhaustive search algorithm. In addition, we investigate the impact of various system parameters in the collaboration decision.

  6. Phosphatidylinositol 3-phosphates-at the interface between cell signalling and membrane traffic.

    Science.gov (United States)

    Marat, Andrea L; Haucke, Volker

    2016-03-15

    Phosphoinositides (PIs) form a minor class of phospholipids with crucial functions in cell physiology, ranging from cell signalling and motility to a role as signposts of compartmental membrane identity. Phosphatidylinositol 3-phosphates are present at the plasma membrane and within the endolysosomal system, where they serve as key regulators of both cell signalling and of intracellular membrane traffic. Here, we provide an overview of the metabolic pathways that regulate cellular synthesis of PI 3-phosphates at distinct intracellular sites and discuss the mechanisms by which these lipids regulate cell signalling and membrane traffic. Finally, we provide a framework for how PI 3-phosphate metabolism is integrated into the cellular network. © 2016 The Authors.

  7. Unveiling Hidden Dynamics of Hippo Signalling: A Systems Analysis

    Directory of Open Access Journals (Sweden)

    Sung-Young Shin

    2016-08-01

    Full Text Available The Hippo signalling pathway has recently emerged as an important regulator of cell apoptosis and proliferation with significant implications in human diseases. In mammals, the pathway contains the core kinases MST1/2, which phosphorylate and activate LATS1/2 kinases. The pro-apoptotic function of the MST/LATS signalling axis was previously linked to the Akt and ERK MAPK pathways, demonstrating that the Hippo pathway does not act alone but crosstalks with other signalling pathways to coordinate network dynamics and cellular outcomes. These crosstalks were characterised by a multitude of complex regulatory mechanisms involving competitive protein-protein interactions and phosphorylation mediated feedback loops. However, how these different mechanisms interplay in different cellular contexts to drive the context-specific network dynamics of Hippo-ERK signalling remains elusive. Using mathematical modelling and computational analysis, we uncovered that the Hippo-ERK network can generate highly diverse dynamical profiles that can be clustered into distinct dose-response patterns. For each pattern, we offered mechanistic explanation that defines when and how the observed phenomenon can arise. We demonstrated that Akt displays opposing, dose-dependent functions towards ERK, which are mediated by the balance between the Raf-1/MST2 protein interaction module and the LATS1 mediated feedback regulation. Moreover, Ras displays a multi-functional role and drives biphasic responses of both MST2 and ERK activities; which are critically governed by the competitive protein interaction between MST2 and Raf-1. Our study represents the first in-depth and systematic analysis of the Hippo-ERK network dynamics and provides a concrete foundation for future studies.

  8. Data-driven quantification of the robustness and sensitivity of cell signaling networks

    International Nuclear Information System (INIS)

    Mukherjee, Sayak; Seok, Sang-Cheol; Vieland, Veronica J; Das, Jayajit

    2013-01-01

    Robustness and sensitivity of responses generated by cell signaling networks has been associated with survival and evolvability of organisms. However, existing methods analyzing robustness and sensitivity of signaling networks ignore the experimentally observed cell-to-cell variations of protein abundances and cell functions or contain ad hoc assumptions. We propose and apply a data-driven maximum entropy based method to quantify robustness and sensitivity of Escherichia coli (E. coli) chemotaxis signaling network. Our analysis correctly rank orders different models of E. coli chemotaxis based on their robustness and suggests that parameters regulating cell signaling are evolutionary selected to vary in individual cells according to their abilities to perturb cell functions. Furthermore, predictions from our approach regarding distribution of protein abundances and properties of chemotactic responses in individual cells based on cell population averaged data are in excellent agreement with their experimental counterparts. Our approach is general and can be used to evaluate robustness as well as generate predictions of single cell properties based on population averaged experimental data in a wide range of cell signaling systems. (paper)

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

    Science.gov (United States)

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

    2010-07-01

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

  10. Coded Network Function Virtualization

    DEFF Research Database (Denmark)

    Al-Shuwaili, A.; Simone, O.; Kliewer, J.

    2016-01-01

    Network function virtualization (NFV) prescribes the instantiation of network functions on general-purpose network devices, such as servers and switches. While yielding a more flexible and cost-effective network architecture, NFV is potentially limited by the fact that commercial off......-the-shelf hardware is less reliable than the dedicated network elements used in conventional cellular deployments. The typical solution for this problem is to duplicate network functions across geographically distributed hardware in order to ensure diversity. In contrast, this letter proposes to leverage channel...... coding in order to enhance the robustness on NFV to hardware failure. The proposed approach targets the network function of uplink channel decoding, and builds on the algebraic structure of the encoded data frames in order to perform in-network coding on the signals to be processed at different servers...

  11. Collective signaling behavior in a networked-oscillator model

    Science.gov (United States)

    Liu, Z.-H.; Hui, P. M.

    2007-09-01

    We propose and study the collective behavior of a model of networked signaling objects that incorporates several ingredients of real-life systems. These ingredients include spatial inhomogeneity with grouping of signaling objects, signal attenuation with distance, and delayed and impulsive coupling between non-identical signaling objects. Depending on the coupling strength and/or time-delay effect, the model exhibits completely, partially, and locally collective signaling behavior. In particular, a correlated signaling (CS) behavior is observed in which there exist time durations when nearly a constant fraction of oscillators in the system are in the signaling state. These time durations are much longer than the duration of a spike when a single oscillator signals, and they are separated by regular intervals in which nearly all oscillators are silent. Such CS behavior is similar to that observed in biological systems such as fireflies, cicadas, crickets, and frogs. The robustness of the CS behavior against noise is also studied. It is found that properly adjusting the coupling strength and noise level could enhance the correlated behavior.

  12. Random Deep Belief Networks for Recognizing Emotions from Speech Signals.

    Science.gov (United States)

    Wen, Guihua; Li, Huihui; Huang, Jubing; Li, Danyang; Xun, Eryang

    2017-01-01

    Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN) can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN) method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

  13. Random Deep Belief Networks for Recognizing Emotions from Speech Signals

    Directory of Open Access Journals (Sweden)

    Guihua Wen

    2017-01-01

    Full Text Available Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

  14. Novel links in the plant TOR kinase signaling network.

    Science.gov (United States)

    Xiong, Yan; Sheen, Jen

    2015-12-01

    Nutrient and energy sensing and signaling mechanisms constitute the most ancient and fundamental regulatory networks to control growth and development in all life forms. The target of rapamycin (TOR) protein kinase is modulated by diverse nutrient, energy, hormone and stress inputs and plays a central role in regulating cell proliferation, growth, metabolism and stress responses from yeasts to plants and animals. Recent chemical, genetic, genomic and metabolomic analyses have enabled significant progress toward molecular understanding of the TOR signaling network in multicellular plants. This review discusses the applications of new chemical tools to probe plant TOR functions and highlights recent findings and predictions on TOR-mediate biological processes. Special focus is placed on novel and evolutionarily conserved TOR kinase effectors as positive and negative signaling regulators that control transcription, translation and metabolism to support cell proliferation, growth and maintenance from embryogenesis to senescence in the plant system. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Secure Real-Time Monitoring and Management of Smart Distribution Grid using Shared Cellular Networks

    DEFF Research Database (Denmark)

    Nielsen, Jimmy Jessen; Ganem, Hervé; Jorguseski, Ljupco

    2017-01-01

    capabilities. Thanks to the advanced measurement devices, management framework, and secure communication infrastructure developed in the FP7 SUNSEED project, the Distribution System Operator (DSO) now has full observability of the energy flows at the medium/low voltage grid. Furthermore, the prosumers are able......, where the smart grid ICT solutions are provided through shared cellular LTE networks....

  16. A Channel Allocation Mechanism for Cellular Networks

    Directory of Open Access Journals (Sweden)

    Chi-Hua Chen

    2017-04-01

    Full Text Available In cellular networks, call blocking causes lower customer satisfaction and economic loss. Therefore, the channel allocation for call block avoidance is an important issue. This study proposes a mechanism that considers the real-time traffic information (e.g., traffic flow and vehicle speed and the user behavior (e.g., call inter-arrival time and call holding time to analyze the adaptable number of communication calls in the specific cell for channel allocation. In experiments about call block probabilities (CBP, this study simulated two cases that are the situations of the whole day and traffic accident. The simulation results show that all CBPs in the scenario of whole day are less than 21.5% by using the proposed mechanism, which is better than using the static channel allocation (SCA mechanism. Moreover, all CBPs in the scenario of traffic accidents are less than 16.5% by using the proposed mechanism, which is better than using the SCA mechanism. Therefore, the proposed mechanism can decrease the number of CBPs effectively.

  17. Cellular-automata-based learning network for pattern recognition

    Science.gov (United States)

    Tzionas, Panagiotis G.; Tsalides, Phillippos G.; Thanailakis, Adonios

    1991-11-01

    Most classification techniques either adopt an approach based directly on the statistical characteristics of the pattern classes involved, or they transform the patterns in a feature space and try to separate the point clusters in this space. An alternative approach based on memory networks has been presented, its novelty being that it can be implemented in parallel and it utilizes direct features of the patterns rather than statistical characteristics. This study presents a new approach for pattern classification using pseudo 2-D binary cellular automata (CA). This approach resembles the memory network classifier in the sense that it is based on an adaptive knowledge based formed during a training phase, and also in the fact that both methods utilize pattern features that are directly available. The main advantage of this approach is that the sensitivity of the pattern classifier can be controlled. The proposed pattern classifier has been designed using 1.5 micrometers design rules for an N-well CMOS process. Layout has been achieved using SOLO 1400. Binary pseudo 2-D hybrid additive CA (HACA) is described in the second section of this paper. The third section describes the operation of the pattern classifier and the fourth section presents some possible applications. The VLSI implementation of the pattern classifier is presented in the fifth section and, finally, the sixth section draws conclusions from the results obtained.

  18. Cellular Neural Network for Real Time Image Processing

    International Nuclear Information System (INIS)

    Vagliasindi, G.; Arena, P.; Fortuna, L.; Mazzitelli, G.; Murari, A.

    2008-01-01

    Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information for plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET)

  19. Energy Efficient Caching in Backhaul-Aware Cellular Networks with Dynamic Content Popularity

    Directory of Open Access Journals (Sweden)

    Jiequ Ji

    2018-01-01

    Full Text Available Caching popular contents at base stations (BSs has been regarded as an effective approach to alleviate the backhaul load and to improve the quality of service. To meet the explosive data traffic demand and to save energy consumption, energy efficiency (EE has become an extremely important performance index for the 5th generation (5G cellular networks. In general, there are two ways for improving the EE for caching, that is, improving the cache-hit rate and optimizing the cache size. In this work, we investigate the energy efficient caching problem in backhaul-aware cellular networks jointly considering these two approaches. Note that most existing works are based on the assumption that the content catalog and popularity are static. However, in practice, content popularity is dynamic. To timely estimate the dynamic content popularity, we propose a method based on shot noise model (SNM. Then we propose a distributed caching policy to improve the cache-hit rate in such a dynamic environment. Furthermore, we analyze the tradeoff between energy efficiency and cache capacity for which an optimization is formulated. We prove its convexity and derive a closed-form optimal cache capacity for maximizing the EE. Simulation results validate the proposed scheme and show that EE can be improved with appropriate choice of cache capacity.

  20. Ion channel signaling influences cellular proliferation and phagocyte activity during axolotl tail regeneration.

    Science.gov (United States)

    Franklin, Brandon M; Voss, S Randal; Osborn, Jeffrey L

    2017-08-01

    Little is known about the potential for ion channels to regulate cellular behaviors during tissue regeneration. Here, we utilized an amphibian tail regeneration assay coupled with a chemical genetic screen to identify ion channel antagonists that altered critical cellular processes during regeneration. Inhibition of multiple ion channels either partially (anoctamin1/Tmem16a, anoctamin2/Tmem16b, K V 2.1, K V 2.2, L-type Ca V channels and H/K ATPases) or completely (GlyR, GABA A R, K V 1.5 and SERCA pumps) inhibited tail regeneration. Partial inhibition of tail regeneration by blocking the calcium activated chloride channels, anoctamin1&2, was associated with a reduction of cellular proliferation in tail muscle and mesenchymal regions. Inhibition of anoctamin 1/2 also altered the post-amputation transcriptional response of p44/42 MAPK signaling pathway genes, including decreased expression of erk1/erk2. We also found that complete inhibition via voltage gated K + channel blockade was associated with diminished phagocyte recruitment to the amputation site. The identification of H + pumps as required for axolotl tail regeneration supports findings in Xenopus and Planaria models, and more generally, the conservation of ion channels as regulators of tissue regeneration. This study provides a preliminary framework for an in-depth investigation of the mechanistic role of ion channels and their potential involvement in regulating cellular proliferation and other processes essential to wound healing, appendage regeneration, and tissue repair. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Brain Network Analysis from High-Resolution EEG Signals

    Science.gov (United States)

    de Vico Fallani, Fabrizio; Babiloni, Fabio

    Over the last decade, there has been a growing interest in the detection of the functional connectivity in the brain from different neuroelectromagnetic and hemodynamic signals recorded by several neuro-imaging devices such as the functional Magnetic Resonance Imaging (fMRI) scanner, electroencephalography (EEG) and magnetoencephalography (MEG) apparatus. Many methods have been proposed and discussed in the literature with the aim of estimating the functional relationships among different cerebral structures. However, the necessity of an objective comprehension of the network composed by the functional links of different brain regions is assuming an essential role in the Neuroscience. Consequently, there is a wide interest in the development and validation of mathematical tools that are appropriate to spot significant features that could describe concisely the structure of the estimated cerebral networks. The extraction of salient characteristics from brain connectivity patterns is an open challenging topic, since often the estimated cerebral networks have a relative large size and complex structure. Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach seems relevant and useful as firstly demonstrated on a set of anatomical brain networks. In those studies, the authors have employed two characteristic measures, the average shortest path L and the clustering index C, to extract respectively the global and local properties of the network structure. They have found that anatomical brain networks exhibit many local connections (i.e. a high C) and few random long distance connections (i.e. a low L). These values identify a particular model that interpolate between a regular

  2. Dynamics of a class of cellular neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Huang Lihong; Huang Chuangxia; Liu Bingwen

    2005-01-01

    Employing Brouwer's fixed point theorem, matrix theory, a continuation theorem of the coincidence degree and inequality analysis, the authors make a further investigation of a class of cellular neural networks with delays (DCNNs) in this Letter. A family of sufficient conditions are given for checking global exponential stability and the existence of periodic solutions of DCNNs. These results have important leading significance in the design and applications of globally stable DCNNs and periodic oscillatory DCNNs. Our results extend and improve some earlier publications

  3. Modularized TGFbeta-Smad Signaling Pathway

    Science.gov (United States)

    Li, Yongfeng; Wang, M.; Carra, C.; Cucinotta, F. A.

    2011-01-01

    The Transforming Growth Factor beta (TGFbeta) signaling pathway is a prominent regulatory signaling pathway controlling various important cellular processes. It can be induced by several factors, including ionizing radiation. It is regulated by Smads in a negative feedback loop through promoting increases in the regulatory Smads in the cell nucleus, and subsequent expression of inhibitory Smad, Smad7 to form a ubiquitin ligase with Smurf targeting active TGF receptors for degradation. In this work, we proposed a mathematical model to study the radiation-induced Smad-regulated TGF signaling pathway. By modularization, we are able to analyze each module (subsystem) and recover the nonlinear dynamics of the entire network system. Meanwhile the excitability, a common feature observed in the biological systems, along the TGF signaling pathway is discussed by mathematical analysis and numerical simulation.

  4. Performance analysis of a handoff scheme for two-tier cellular CDMA networks

    Directory of Open Access Journals (Sweden)

    Ahmed Hamad

    2011-07-01

    Full Text Available A two-tier model is used in cellular networks to improve the Quality of Service (QoS, namely to reduce the blocking probability of new calls and the forced termination probability of ongoing calls. One tier, the microcells, is used for slow or stationary users, and the other, the macrocell, is used for high speed users. In Code-Division Multiple-Access (CDMA cellular systems, soft handoffs are supported, which provides ways for further QoS improvement. In this paper, we introduce such a way; namely, a channel borrowing scheme used in conjunction with a First-In-First-Out (FIFO queue in the macrocell tier. A multidimensional Markov chain to model the resulting system is established, and an iterative technique to find the steady-state probability distribution is utilized. This distribution is then used to find the performance measures of interest: new call blocking probability, and forced termination probability.

  5. Effect of placement of droop based generators in distribution network on small signal stability margin and network loss

    DEFF Research Database (Denmark)

    Dheer, D.K.; Doolla, S.; Bandyopadhyay, S.

    2017-01-01

    , small signal stability margin is on the fore. The present research studied the effect of location of droop-controlled DGs on small signal stability margin and network loss on a modified IEEE 13 bus system, an IEEE 33-bus distribution system and a practical 22-bus radial distribution network. A complete...... loss and stability margin is further investigated by identifying the Pareto fronts for modified IEEE 13 bus, IEEE 33 and practical 22-bus radial distribution network with application of Reference point based Non-dominated Sorting Genetic Algorithm (R-NSGA). Results were validated by time domain......For a utility-connected system, issues related to small signal stability with Distributed Generators (DGs) are insignificant due to the presence of a very strong grid. Optimally placed sources in utility connected microgrid system may not be optimal/stable in islanded condition. Among others issues...

  6. Biophysical constraints on the computational capacity of biochemical signaling networks

    Science.gov (United States)

    Wang, Ching-Hao; Mehta, Pankaj

    Biophysics fundamentally constrains the computations that cells can carry out. Here, we derive fundamental bounds on the computational capacity of biochemical signaling networks that utilize post-translational modifications (e.g. phosphorylation). To do so, we combine ideas from the statistical physics of disordered systems and the observation by Tony Pawson and others that the biochemistry underlying protein-protein interaction networks is combinatorial and modular. Our results indicate that the computational capacity of signaling networks is severely limited by the energetics of binding and the need to achieve specificity. We relate our results to one of the theoretical pillars of statistical learning theory, Cover's theorem, which places bounds on the computational capacity of perceptrons. PM and CHW were supported by a Simons Investigator in the Mathematical Modeling of Living Systems Grant, and NIH Grant No. 1R35GM119461 (both to PM).

  7. Traffic analysis and signal processing in optical packet switched networks

    DEFF Research Database (Denmark)

    Fjelde, Tina

    2002-01-01

    /s optical packet switched network exploiting the best of optics and electronics, is used as a thread throughout the thesis. An overview of the DAVID network architecture is given, focussing on the MAN and WAN architecture as well as the MPLS-based network hierarchy. Subsequently, the traffic performance...... of the DAVID core optical packet router, which exploits wavelength conversion and fibre delay-line buffers for contention resolution, is analysed using a numerical model developed for that purpose. The robustness of the shared recirculating loop buffer with respect to´bursty traffic is demonstrated...... the injection of an additional clock signal into the IWC is presented. Results show very good transmission capabilities combined with a high-speed response. It is argued that signal regeneration is an inherent attribute of the IWC employed as a wavelength converter due to the sinusoidal transfer function...

  8. Discovery of intramolecular signal transduction network based on a new protein dynamics model of energy dissipation.

    Directory of Open Access Journals (Sweden)

    Cheng-Wei Ma

    Full Text Available A novel approach to reveal intramolecular signal transduction network is proposed in this work. To this end, a new algorithm of network construction is developed, which is based on a new protein dynamics model of energy dissipation. A key feature of this approach is that direction information is specified after inferring protein residue-residue interaction network involved in the process of signal transduction. This enables fundamental analysis of the regulation hierarchy and identification of regulation hubs of the signaling network. A well-studied allosteric enzyme, E. coli aspartokinase III, is used as a model system to demonstrate the new method. Comparison with experimental results shows that the new approach is able to predict all the sites that have been experimentally proved to desensitize allosteric regulation of the enzyme. In addition, the signal transduction network shows a clear preference for specific structural regions, secondary structural types and residue conservation. Occurrence of super-hubs in the network indicates that allosteric regulation tends to gather residues with high connection ability to collectively facilitate the signaling process. Furthermore, a new parameter of propagation coefficient is defined to determine the propagation capability of residues within a signal transduction network. In conclusion, the new approach is useful for fundamental understanding of the process of intramolecular signal transduction and thus has significant impact on rational design of novel allosteric proteins.

  9. Coupling switches and oscillators as a means to shape cellular signals in biomolecular systems

    International Nuclear Information System (INIS)

    Zhou, Peipei; Cai, Shuiming; Liu, Zengrong; Chen, Luonan; Wang, Ruiqi

    2013-01-01

    To understand how a complex biomolecular network functions, a decomposition or a reconstruction process of the network is often needed so as to provide new insights into the regulatory mechanisms underlying various dynamical behaviors and also to gain qualitative knowledge of the network. Unfortunately, it seems that there are still no general rules on how to decompose a complex network into simple modules. An alternative resolution is to decompose a complex network into small modules or subsystems with specified functions such as switches and oscillators and then integrate them by analyzing the interactions between them. The main idea of this approach can be illustrated by considering a bidirectionally coupled network in this paper, i.e., coupled Toggle switch and Repressilator, and analyzing the occurrence of various dynamics, although the theoretical principle may hold for a general class of networks. We show that various biomolecular signals can be shaped by regulating the coupling between the subsystems. The approach presented here can be expected to simplify and analyze even more complex biological networks

  10. Coupling switches and oscillators as a means to shape cellular signals in biomolecular systems

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Peipei [Institute of Systems Biology, Shanghai University, Shanghai 200444 (China); Faculty of Science, Jiangsu University, Zhenjiang, Jiangsu 212013 (China); Cai, Shuiming [Faculty of Science, Jiangsu University, Zhenjiang, Jiangsu 212013 (China); Liu, Zengrong [Institute of Systems Biology, Shanghai University, Shanghai 200444 (China); Chen, Luonan [Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Center for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031 (China); Collaborative Research Center for Innovative Mathematical Modeling, Institute of Industrial Science, University of Tokyo, Tokyo 153-8505 (Japan); Wang, Ruiqi [Institute of Systems Biology, Shanghai University, Shanghai 200444 (China)

    2013-05-15

    To understand how a complex biomolecular network functions, a decomposition or a reconstruction process of the network is often needed so as to provide new insights into the regulatory mechanisms underlying various dynamical behaviors and also to gain qualitative knowledge of the network. Unfortunately, it seems that there are still no general rules on how to decompose a complex network into simple modules. An alternative resolution is to decompose a complex network into small modules or subsystems with specified functions such as switches and oscillators and then integrate them by analyzing the interactions between them. The main idea of this approach can be illustrated by considering a bidirectionally coupled network in this paper, i.e., coupled Toggle switch and Repressilator, and analyzing the occurrence of various dynamics, although the theoretical principle may hold for a general class of networks. We show that various biomolecular signals can be shaped by regulating the coupling between the subsystems. The approach presented here can be expected to simplify and analyze even more complex biological networks.

  11. The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

    Science.gov (United States)

    Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

    2009-02-01

    Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

  12. Cellular Dynamics Revealed by Digital Holographic Microscopy☆

    KAUST Repository

    Marquet, P.

    2016-11-22

    Digital holographic microscopy (DHM) is a new optical method that provides, without the use of any contrast agent, real-time, three-dimensional images of transparent living cells, with an axial sensitivity of a few tens of nanometers. They result from the hologram numerical reconstruction process, which permits a sub wavelength calculation of the phase shift, produced on the transmitted wave front, by the optically probed cells, namely the quantitative phase signal (QPS). Specifically, in addition to measurements of cellular surface morphometry and intracellular refractive index (RI), various biophysical cellular parameters including dry mass, absolute volume, membrane fluctuations at the nanoscale and biomechanical properties, transmembrane water permeability as swell as current, can be derived from the QPS. This article presents how quantitative phase DHM (QP-DHM) can explored cell dynamics at the nanoscale with a special attention to both the study of neuronal dynamics and the optical resolution of local neuronal network.

  13. Cellular Dynamics Revealed by Digital Holographic Microscopy☆

    KAUST Repository

    Marquet, P.; Depeursinge, Christian; Jourdain, P.

    2016-01-01

    Digital holographic microscopy (DHM) is a new optical method that provides, without the use of any contrast agent, real-time, three-dimensional images of transparent living cells, with an axial sensitivity of a few tens of nanometers. They result from the hologram numerical reconstruction process, which permits a sub wavelength calculation of the phase shift, produced on the transmitted wave front, by the optically probed cells, namely the quantitative phase signal (QPS). Specifically, in addition to measurements of cellular surface morphometry and intracellular refractive index (RI), various biophysical cellular parameters including dry mass, absolute volume, membrane fluctuations at the nanoscale and biomechanical properties, transmembrane water permeability as swell as current, can be derived from the QPS. This article presents how quantitative phase DHM (QP-DHM) can explored cell dynamics at the nanoscale with a special attention to both the study of neuronal dynamics and the optical resolution of local neuronal network.

  14. On Green Cognitive Radio Cellular Networks: Dynamic Spectrum and Operation Management

    KAUST Repository

    Sboui, Lokman; Ghazzai, Hakim; Rezki, Zouheir; Alouini, Mohamed-Slim

    2016-01-01

    We study a profit maximization problem related to cognitive radio cellular networks in an environmentally- friendly framework. The objective of the primary network (PN) and secondary network (SN) is to maximize their profits while respecting a certain carbon dioxide (CO2) emissions threshold. In this study, the PN can switch off some of its base stations (BSs) powered by mircogrids, and hence leases the spectrum in the corresponding cells, to reduce its footprint. The corresponding users are roamed to the SN infrastructure. In return, the SN receives a certain roaming cost and its users can freely exploit the spectrum. We study two scenarios in which the profits are either separately or jointly maximized. In the disjoint maximization problem, two low complexity algorithms for PN and SN BS on/off switching are proposed to maximize the profit per CO2 emissions utility and determine the amount of the shared bandwidth. In the joint maximization approach, the low complexity algorithm is based on maximizing the sum of weighted profits per CO2. Selected numerical results illustrate the collaboration performance versus various system parameters. We show that the proposed algorithms achieve performances close to those obtained with the exhaustive search method, and that the roaming price and the renewable energy availability are crucial parameters that control the collaboration of both networks.

  15. On Green Cognitive Radio Cellular Networks: Dynamic Spectrum and Operation Management

    KAUST Repository

    Sboui, Lokman

    2016-07-18

    We study a profit maximization problem related to cognitive radio cellular networks in an environmentally- friendly framework. The objective of the primary network (PN) and secondary network (SN) is to maximize their profits while respecting a certain carbon dioxide (CO2) emissions threshold. In this study, the PN can switch off some of its base stations (BSs) powered by mircogrids, and hence leases the spectrum in the corresponding cells, to reduce its footprint. The corresponding users are roamed to the SN infrastructure. In return, the SN receives a certain roaming cost and its users can freely exploit the spectrum. We study two scenarios in which the profits are either separately or jointly maximized. In the disjoint maximization problem, two low complexity algorithms for PN and SN BS on/off switching are proposed to maximize the profit per CO2 emissions utility and determine the amount of the shared bandwidth. In the joint maximization approach, the low complexity algorithm is based on maximizing the sum of weighted profits per CO2. Selected numerical results illustrate the collaboration performance versus various system parameters. We show that the proposed algorithms achieve performances close to those obtained with the exhaustive search method, and that the roaming price and the renewable energy availability are crucial parameters that control the collaboration of both networks.

  16. A new traffic control design method for large networks with signalized intersections

    Science.gov (United States)

    Leininger, G. G.; Colony, D. C.; Seldner, K.

    1979-01-01

    The paper presents a traffic control design technique for application to large traffic networks with signalized intersections. It is shown that the design method adopts a macroscopic viewpoint to establish a new traffic modelling procedure in which vehicle platoons are subdivided into main stream queues and turning queues. Optimization of the signal splits minimizes queue lengths in the steady state condition and improves traffic flow conditions, from the viewpoint of the traveling public. Finally, an application of the design method to a traffic network with thirty-three signalized intersections is used to demonstrate the effectiveness of the proposed technique.

  17. A Utility-Based Downlink Radio Resource Allocation for Multiservice Cellular DS-CDMA Networks

    Directory of Open Access Journals (Sweden)

    Mahdi Shabany

    2007-03-01

    Full Text Available A novel framework is proposed to model downlink resource allocation problem in multiservice direct-sequence code division multiple-access (DS-CDMA cellular networks. This framework is based on a defined utility function, which leads to utilizing the network resources in a more efficient way. This utility function quantifies the degree of utilization of resources. As a matter of fact, using the defined utility function, users' channel fluctuations and their delay constraints along with the load conditions of all BSs are all taken into consideration. Unlike previous works, we solve the problem with the general objective of maximizing the total network utility instead of maximizing the achieved utility of each base station (BS. It is shown that this problem is equivalent to finding the optimum BS assignment throughout the network, which is mapped to a multidimensional multiple-choice knapsack problem (MMKP. Since MMKP is NP-hard, a polynomial-time suboptimal algorithm is then proposed to develop an efficient base-station assignment. Simulation results indicate a significant performance improvement in terms of achieved utility and packet drop ratio.

  18. CRF2 signaling is a novel regulator of cellular adhesion and migration in colorectal cancer cells.

    Science.gov (United States)

    Ducarouge, Benjamin; Pelissier-Rota, Marjolaine; Lainé, Michèle; Cristina, Nadine; Vachez, Yvan; Scoazec, Jean-Yves; Bonaz, Bruno; Jacquier-Sarlin, Muriel

    2013-01-01

    Stress has been proposed to be a tumor promoting factor through the secretion of specific neuromediators, such as Urocortin2 and 3 (Ucn2/3), however its role in colorectal cancer (CRC) remains elusive. We observed that Ucn2/3 and their receptor the Corticotropin Releasing Factor receptor 2 (CRF2) were up-regulated in high grade and poorly differentiated CRC. This suggests a role for CRF2 in the loss of cellular organization and tumor progression. Using HT-29 and SW620 cells, two CRC cell lines differing in their abilities to perform cell-cell contacts, we found that CRF2 signals through Src/ERK pathway to induce the alteration of cell-cell junctions and the shuttle of p120ctn and Kaiso in the nucleus. In HT-29 cells, this signaling pathway also leads to the remodeling of cell adhesion by i) the phosphorylation of Focal Adhesion Kinase and ii) a modification of actin cytoskeleton and focal adhesion complexes. These events stimulate cell migration and invasion. In conclusion, our findings indicate that CRF2 signaling controls cellular organization and may promote metastatic potential of human CRC cells through an epithelial-mesenchymal transition like process. This contributes to the comprehension of the tumor-promoting effects of stress molecules and designates Ucn2/3-CRF2 tandem as a target to prevent CRC progression and aggressiveness.

  19. 1st International Conference on Signal, Networks, Computing, and Systems

    CERN Document Server

    Mohapatra, Durga; Nagar, Atulya; Sahoo, Manmath

    2016-01-01

    The book is a collection of high-quality peer-reviewed research papers presented in the first International Conference on Signal, Networks, Computing, and Systems (ICSNCS 2016) held at Jawaharlal Nehru University, New Delhi, India during February 25–27, 2016. The book is organized in to two volumes and primarily focuses on theory and applications in the broad areas of communication technology, computer science and information security. The book aims to bring together the latest scientific research works of academic scientists, professors, research scholars and students in the areas of signal, networks, computing and systems detailing the practical challenges encountered and the solutions adopted.

  20. Outer-totalistic cellular automata on graphs

    International Nuclear Information System (INIS)

    Marr, Carsten; Huett, Marc-Thorsten

    2009-01-01

    We present an intuitive formalism for implementing cellular automata on arbitrary topologies. By that means, we identify a symmetry operation in the class of elementary cellular automata. Moreover, we determine the subset of topologically sensitive elementary cellular automata and find that the overall number of complex patterns decreases under increasing neighborhood size in regular graphs. As exemplary applications, we apply the formalism to complex networks and compare the potential of scale-free graphs and metabolic networks to generate complex dynamics

  1. Spatio-temporal remodeling of functional membrane microdomains organizes the signaling networks of a bacterium.

    Directory of Open Access Journals (Sweden)

    Johannes Schneider

    2015-04-01

    Full Text Available Lipid rafts are membrane microdomains specialized in the regulation of numerous cellular processes related to membrane organization, as diverse as signal transduction, protein sorting, membrane trafficking or pathogen invasion. It has been proposed that this functional diversity would require a heterogeneous population of raft domains with varying compositions. However, a mechanism for such diversification is not known. We recently discovered that bacterial membranes organize their signal transduction pathways in functional membrane microdomains (FMMs that are structurally and functionally similar to the eukaryotic lipid rafts. In this report, we took advantage of the tractability of the prokaryotic model Bacillus subtilis to provide evidence for the coexistence of two distinct families of FMMs in bacterial membranes, displaying a distinctive distribution of proteins specialized in different biological processes. One family of microdomains harbors the scaffolding flotillin protein FloA that selectively tethers proteins specialized in regulating cell envelope turnover and primary metabolism. A second population of microdomains containing the two scaffolding flotillins, FloA and FloT, arises exclusively at later stages of cell growth and specializes in adaptation of cells to stationary phase. Importantly, the diversification of membrane microdomains does not occur arbitrarily. We discovered that bacterial cells control the spatio-temporal remodeling of microdomains by restricting the activation of FloT expression to stationary phase. This regulation ensures a sequential assembly of functionally specialized membrane microdomains to strategically organize signaling networks at the right time during the lifespan of a bacterium.

  2. The Digital Age of Mobile Cellular Network in Germany and China: Policies, Technologies and Markets (Part Ⅱ)

    Institute of Scientific and Technical Information of China (English)

    Mingtao Shi

    2009-01-01

    The German Postal Reform Ⅰ in 1989 introduced competition in the mobile cellular market. German cellular operators, DeTeMobil, Mannesmann, E-Plus and VIAG Interkom, built D1-, D2-, El-and E2-Netze based on GSM standards made in Europe. China Unicom was created in 1994 and China Telecom was separated from MPT in 1995. China Telecom and China Unicom competed in a duopoly from the mid-1990s onwards and the cellular services provided by them also rely on GSM standards. China Telecom additionally deployed XLT technology (PHS) from the late 1990s onwards. While DeTeMobil and Mannesmann conquered approximately 80%-90% of the market throughout the 1990s and were the two dominant market players in Germany, China's cellular market was mainly controlled by China Mobile. In Germany, prices related to cellular technology continued the downwards trend as a major result of the process of deregulation, liberalisation and competition. In China, price wars had led to significant price reductions in the cellular market. Although network operators in both countries strived to deliver differentiated cellular services, the two national markets in the 1990s were visibly shaped by product homogeneity.

  3. Programs for control of an analog-signal switching network

    International Nuclear Information System (INIS)

    D'Ottavio, T.; Enriquez, R.; Katz, R.; Skelly, J.

    1989-01-01

    A suite of programs has been developed to control the network of analog-signal switching multiplexers in the AGS complex. The software is driven by a relational database which describes the architecture of the multiplexer tree and the set of available analog signals. Signals are routed through a three-layer multiplexer tree, to be made available at four consoles each with three 4-trace oscilloscopes. A menu-structured operator interface program is available at each console, to accept requests to route any available analog signal to any of that console's 12 oscilloscope traces. A common routing-server program provides automatic routing-server program provides automatic routing of requested signals through the layers of multiplexers, maintaining a reservation database to denote free and in-use trunks. Expansion of the analog signal system is easily accommodated in software by adding new signals, trunks, multiplexers, or consoles to the database. Programmatic control of the triggering signals for each of the oscilloscopes is also provided. 3 refs., 4 figs., 3 tabs

  4. Anomalous Signal Detection in ELF Band Electromagnetic Wave using Multi-layer Neural Network with Wavelet Decomposition

    Science.gov (United States)

    Itai, Akitoshi; Yasukawa, Hiroshi; Takumi, Ichi; Hata, Masayasu

    It is well known that electromagnetic waves radiated from the earth's crust are useful for predicting earthquakes. We analyze the electromagnetic waves received at the extremely low frequency band of 223Hz. These observed signals contain the seismic radiation from the earth's crust, but also include several undesired signals. Our research focuses on the signal detection technique to identify an anomalous signal corresponding to the seismic radiation in the observed signal. Conventional anomalous signal detections lack a wide applicability due to their assumptions, e.g. the digital data have to be observed at the same time or the same sensor. In order to overcome the limitation related to the observed signal, we proposed the anomalous signals detection based on a multi-layer neural network which is trained by digital data observed during a span of a day. In the neural network approach, training data do not need to be recorded at the same place or the same time. However, some noises, which have a large amplitude, are detected as the anomalous signal. This paper develops a multi-layer neural network to decrease the false detection of the anomalous signal from the electromagnetic wave. The training data for the proposed network is the decomposed signal of the observed signal during several days, since the seismic radiations are often recorded from several days to a couple of weeks. Results show that the proposed neural network is useful to achieve the accurate detection of the anomalous signal that indicates seismic activity.

  5. Design principles of nuclear receptor signaling: how complex networking improves signal transduction

    Science.gov (United States)

    Kolodkin, Alexey N; Bruggeman, Frank J; Plant, Nick; Moné, Martijn J; Bakker, Barbara M; Campbell, Moray J; van Leeuwen, Johannes P T M; Carlberg, Carsten; Snoep, Jacky L; Westerhoff, Hans V

    2010-01-01

    The topology of nuclear receptor (NR) signaling is captured in a systems biological graphical notation. This enables us to identify a number of ‘design' aspects of the topology of these networks that might appear unnecessarily complex or even functionally paradoxical. In realistic kinetic models of increasing complexity, calculations show how these features correspond to potentially important design principles, e.g.: (i) cytosolic ‘nuclear' receptor may shuttle signal molecules to the nucleus, (ii) the active export of NRs may ensure that there is sufficient receptor protein to capture ligand at the cytoplasmic membrane, (iii) a three conveyor belts design dissipating GTP-free energy, greatly aids response, (iv) the active export of importins may prevent sequestration of NRs by importins in the nucleus and (v) the unspecific nature of the nuclear pore may ensure signal-flux robustness. In addition, the models developed are suitable for implementation in specific cases of NR-mediated signaling, to predict individual receptor functions and differential sensitivity toward physiological and pharmacological ligands. PMID:21179018

  6. Global stability of almost periodic solution of shunting inhibitory cellular neural networks with variable coefficients

    International Nuclear Information System (INIS)

    Chen Ling; Zhao Hongyong

    2008-01-01

    The paper investigates the almost periodicity of shunting inhibitory cellular neural networks with delays and variable coefficients. Several sufficient conditions are established for the existence and globally exponential stability of almost periodic solutions by employing fixed point theorem and differential inequality technique. The results of this paper are new and they complement previously known results

  7. Identification of cellular responses to low-dose radiation by antibody array in human B-lymphoblasts IM-9 cells

    Energy Technology Data Exchange (ETDEWEB)

    Eom, Hyeon Soo; Kim, Ji Young; Nam, Seon Young [Low-dose Radiation Research Team, Radiation Health Institute, Korea Hydro and Nuclear Power Co. LTD., Seoul (Korea, Republic of)

    2017-04-15

    The low-dose radiation (LDR)-induced various responses can reduce genetic mutation, enhance cell survival, and increase infection resistance (1). The antibody array for global analysis of phosphorylated proteins might be very useful to study signaling networks of LDR-induced cellular responses (2). Therefore, global analysis of phospho- proteins in cells exposed to radiation is important to understand the signaling mechanisms induced by changes of protein phosphorylation which lead to various biological effects by radiation. The aim is to explore the possibility of LDR-specific signaling for various beneficial effects and elucidate the potential signaling pathways representing LDR responses. Our results suggest that LDR did not affect cell death and that the increased proteins phosphorylation by LDR might be involved in various cellular responses for cell homeostasis. These results might be useful to further studies aimed at investigating potential regulatory markers that represent responses to LDR.

  8. Identification of cellular responses to low-dose radiation by antibody array in human B-lymphoblasts IM-9 cells

    International Nuclear Information System (INIS)

    Eom, Hyeon Soo; Kim, Ji Young; Nam, Seon Young

    2017-01-01

    The low-dose radiation (LDR)-induced various responses can reduce genetic mutation, enhance cell survival, and increase infection resistance (1). The antibody array for global analysis of phosphorylated proteins might be very useful to study signaling networks of LDR-induced cellular responses (2). Therefore, global analysis of phospho- proteins in cells exposed to radiation is important to understand the signaling mechanisms induced by changes of protein phosphorylation which lead to various biological effects by radiation. The aim is to explore the possibility of LDR-specific signaling for various beneficial effects and elucidate the potential signaling pathways representing LDR responses. Our results suggest that LDR did not affect cell death and that the increased proteins phosphorylation by LDR might be involved in various cellular responses for cell homeostasis. These results might be useful to further studies aimed at investigating potential regulatory markers that represent responses to LDR

  9. CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components.

    Science.gov (United States)

    Heberle, Henry; Carazzolle, Marcelo Falsarella; Telles, Guilherme P; Meirelles, Gabriela Vaz; Minghim, Rosane

    2017-09-13

    The advent of "omics" science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability. Here we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB. CellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.

  10. Tri Band Dual Polarized Patch Antenna System For Next Generation Cellular Networks

    Directory of Open Access Journals (Sweden)

    Syed Daniyal Ali Shah

    2017-12-01

    Full Text Available In fifth generation networks much emphasis is given to reduce the handset and base station sizes while incorporating even more features for ubiquitous connectivity. Polarization diversity is one of the methods in which a single multi-polarized antenna brings the advantages of antenna diversity. The multiband handset antennas can be made dual-polarized for improved compensation of fading effects of propagation environment especially in terrestrial bands. This paper focuses on the outcomes of the development of a horizontal and vertical polarized patch antenna scheme that operates on 3 bands 900 MHz 1.8 GHz and 2.4 GHz. The antenna system is tested for gain directivity reflection loss polarization radiation pattern and other parameters. The results are published and found are found to satisfy the requirements of cellular and data communication networks in the specified bands.

  11. STATISTIC MODEL OF DYNAMIC DELAY AND DROPOUT ON CELLULAR DATA NETWORKED CONTROL SYSTEM

    Directory of Open Access Journals (Sweden)

    MUHAMMAD A. MURTI

    2017-07-01

    Full Text Available Delay and dropout are important parameters influence overall control performance in Networked Control System (NCS. The goal of this research is to find a model of delay and dropout of data communication link in the NCS. Experiments have been done in this research to a water level control of boiler tank as part of the NCS based on internet communication network using High Speed Packet Access (HSPA cellular technology. By this experiments have been obtained closed-loop system response as well as data delay and dropout of data packets. This research contributes on modeling of the NCS which is combination of controlled plant and data communication link. Another contribution is statistical model of delay and dropout on the NCS.

  12. Cellular neural network to the spherical harmonics approximation of neutron transport equation in x–y geometry

    International Nuclear Information System (INIS)

    Pirouzmand, Ahmad; Hadad, Kamal

    2012-01-01

    Highlights: ► This paper describes the solution of time-dependent neutron transport equation. ► We use a novel method based on cellular neural networks (CNNs) coupled with the spherical harmonics method. ► We apply the CNN model to simulate step and ramp perturbation transients in a core. ► The accuracy and capabilities of the CNN model are examined for x–y geometry. - Abstract: In an earlier paper we utilized a novel method using cellular neural networks (CNNs) coupled with spherical harmonics method to solve the steady state neutron transport equation in x–y geometry. Here, the previous work is extended to the study of time-dependent neutron transport equation. To achieve this goal, an equivalent electrical circuit based on a second-order form of time-dependent neutron transport equation and one equivalent group of neutron precursor density is obtained by the CNN method. The CNN model is used to simulate step and ramp perturbation transients in a typical 2D core.

  13. Quantitative Analysis of Signaling Networks across Differentially Embedded Tumors Highlights Interpatient Heterogeneity in Human Glioblastoma

    Science.gov (United States)

    2015-01-01

    Glioblastoma multiforme (GBM) is the most aggressive malignant primary brain tumor, with a dismal mean survival even with the current standard of care. Although in vitro cell systems can provide mechanistic insight into the regulatory networks governing GBM cell proliferation and migration, clinical samples provide a more physiologically relevant view of oncogenic signaling networks. However, clinical samples are not widely available and may be embedded for histopathologic analysis. With the goal of accurately identifying activated signaling networks in GBM tumor samples, we investigated the impact of embedding in optimal cutting temperature (OCT) compound followed by flash freezing in LN2 vs immediate flash freezing (iFF) in LN2 on protein expression and phosphorylation-mediated signaling networks. Quantitative proteomic and phosphoproteomic analysis of 8 pairs of tumor specimens revealed minimal impact of the different sample processing strategies and highlighted the large interpatient heterogeneity present in these tumors. Correlation analyses of the differentially processed tumor sections identified activated signaling networks present in selected tumors and revealed the differential expression of transcription, translation, and degradation associated proteins. This study demonstrates the capability of quantitative mass spectrometry for identification of in vivo oncogenic signaling networks from human tumor specimens that were either OCT-embedded or immediately flash-frozen. PMID:24927040

  14. Signaling network of the Btk family kinases.

    Science.gov (United States)

    Qiu, Y; Kung, H J

    2000-11-20

    The Btk family kinases represent new members of non-receptor tyrosine kinases, which include Btk/Atk, Itk/Emt/Tsk, Bmx/Etk, and Tec. They are characterized by having four structural modules: PH (pleckstrin homology) domain, SH3 (Src homology 3) domain, SH2 (Src homology 2) domain and kinase (Src homology 1) domain. Increasing evidence suggests that, like Src-family kinases, Btk family kinases play central but diverse modulatory roles in various cellular processes. They participate in signal transduction in response to virtually all types of extracellular stimuli which are transmitted by growth factor receptors, cytokine receptors, G-protein coupled receptors, antigen-receptors and integrins. They are regulated by many non-receptor tyrosine kinases such as Src, Jak, Syk and FAK family kinases. In turn, they regulate many of major signaling pathways including those of PI3K, PLCgamma and PKC. Both genetic and biochemical approaches have been used to dissect the signaling pathways and elucidate their roles in growth, differentiation and apoptosis. An emerging new role of this family of kinases is cytoskeletal reorganization and cell motility. The physiological importance of these kinases was amply demonstrated by their link to the development of immunodeficiency diseases, due to germ-line mutations. The present article attempts to review the structure and functions of Btk family kinases by summarizing our current knowledge on the interacting partners associated with the different modules of the kinases and the diverse signaling pathways in which they are involved.

  15. Allosteric conformational barcodes direct signaling in the cell.

    Science.gov (United States)

    Nussinov, Ruth; Ma, Buyong; Tsai, Chung-Jung; Csermely, Peter

    2013-09-03

    The cellular network is highly interconnected. Pathways merge and diverge. They proceed through shared proteins and may change directions. How are cellular pathways controlled and their directions decided, coded, and read? These questions become particularly acute when we consider that a small number of pathways, such as signaling pathways that regulate cell fates, cell proliferation, and cell death in development, are extensively exploited. This review focuses on these signaling questions from the structural standpoint and discusses the literature in this light. All co-occurring allosteric events (including posttranslational modifications, pathogen binding, and gain-of-function mutations) collectively tag the protein functional site with a unique barcode. The barcode shape is read by an interacting molecule, which transmits the signal. A conformational barcode provides an intracellular address label, which selectively favors binding to one partner and quenches binding to others, and, in this way, determines the pathway direction, and, eventually, the cell's response and fate. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. Alleviate Cellular Congestion Through Opportunistic Trough Filling

    Directory of Open Access Journals (Sweden)

    Yichuan Wang

    2014-04-01

    Full Text Available The demand for cellular data service has been skyrocketing since the debut of data-intensive smart phones and touchpads. However, not all data are created equal. Many popular applications on mobile devices, such as email synchronization and social network updates, are delay tolerant. In addition, cellular load varies significantly in both large and small time scales. To alleviate network congestion and improve network performance, we present a set of opportunistic trough filling schemes that leverage the time-variation of network congestion and delay-tolerance of certain traffic in this paper. We consider average delay, deadline, and clearance time as the performance metrics. Simulation results show promising performance improvement over the standard schemes. The work shed lights on addressing the pressing issue of cellular overload.

  17. Increasing the coverage area through relay node deployment in long term evolution advanced cellular networks

    Science.gov (United States)

    Aldhaibani, Jaafar A.; Ahmad, R. B.; Yahya, A.; Azeez, Suzan A.

    2015-05-01

    Wireless multi-hop relay networks have become very important technologies in mobile communications. These networks ensure high throughput and coverage extension with a low cost. The poor capacity at cell edges is not enough to meet with growing demand of high capacity and throughput irrespective of user's placement in the cellular network. In this paper we propose optimal placement of relay node that provides maximum achievable rate at users and enhances the throughput and coverage at cell edge region. The proposed scheme is based on the outage probability at users and taken on account the interference between nodes. Numerical analyses along with simulation results indicated there are an improvement in capacity for users at the cell edge is 40% increment from all cell capacity.

  18. Dissection of the insulin signaling pathway via quantitative phosphoproteomics

    DEFF Research Database (Denmark)

    Krüger, Marcus; Kratchmarova, Irina; Blagoev, Blagoy

    2008-01-01

    spectrum of the tyrosine phosphorylation cascade, we have defined the tyrosine-phosphoproteome of the insulin signaling pathway, using high resolution mass spectrometry in combination with phosphotyrosine immunoprecipitation and stable isotope labeling by amino acids in cell culture (SILAC......The insulin signaling pathway is of pivotal importance in metabolic diseases, such as diabetes, and in cellular processes, such as aging. Insulin activates a tyrosine phosphorylation cascade that branches to create a complex network affecting multiple biological processes. To understand the full...

  19. Characterization of Radar Signals Using Neural Networks

    Science.gov (United States)

    1990-12-01

    e***e*e*eeeeeeeeeeeesseeeeeese*eee*e*e************s /* Function Name: load.input.ptterns Number: 4.1 /* Description: This function determines wether ...XSE.last.layer Number: 8.5 */ /* Description: The function determines wether to backpropate the *f /* parameter by the sigmoidal or linear update...Sigmoidal Function," Mathematics of Control, Signals and Systems, 2:303-314 (March 1989). 6. Dayhoff, Judith E. Neural Network Architectures. New York: Van

  20. Cellular Signaling Pathway Alterations and Potential Targeted Therapies for Medullary Thyroid Carcinoma

    Directory of Open Access Journals (Sweden)

    Serena Giunti

    2013-01-01

    Full Text Available Parafollicular C-cell-derived medullary thyroid cancer (MTC comprises 3% to 4% of all thyroid cancers. While cytotoxic treatments have been shown to have limited efficacy, targeted molecular therapies that inhibit rearranged during transfection (RET and other tyrosine kinase receptors that are mainly involved in angiogenesis have shown great promise in the treatment of metastatic or locally advanced MTC. Multi-tyrosine kinase inhibitors such as vandetanib, which is already approved for the treatment of progressive MTC, and cabozantinib have shown distinct advantages with regard to rates of disease response and control. However, these types of tyrosine kinase inhibitor compounds are able to concurrently block several types of targets, which limits the understanding of RET as a specific target. Moreover, important resistances to tyrosine kinase inhibitors can occur, which limit the long-term efficacy of these treatments. Deregulated cellular signaling pathways and genetic alterations in MTC, particularly the activation of the RAS/mammalian target of rapamycin (mTOR cascades and RET crosstalk signaling, are now emerging as novel and potentially promising therapeutic treatments for aggressive MTC.