WorldWideScience

Sample records for multiple biomolecular networks

  1. Stochastic Simulation of Biomolecular Reaction Networks Using the Biomolecular Network Simulator Software

    National Research Council Canada - National Science Library

    Frazier, John; Chusak, Yaroslav; Foy, Brent

    2008-01-01

    .... The software uses either exact or approximate stochastic simulation algorithms for generating Monte Carlo trajectories that describe the time evolution of the behavior of biomolecular reaction networks...

  2. Aligning Biomolecular Networks Using Modular Graph Kernels

    Science.gov (United States)

    Towfic, Fadi; Greenlee, M. Heather West; Honavar, Vasant

    Comparative analysis of biomolecular networks constructed using measurements from different conditions, tissues, and organisms offer a powerful approach to understanding the structure, function, dynamics, and evolution of complex biological systems. We explore a class of algorithms for aligning large biomolecular networks by breaking down such networks into subgraphs and computing the alignment of the networks based on the alignment of their subgraphs. The resulting subnetworks are compared using graph kernels as scoring functions. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit. Our experiments using Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository of protein-protein interaction data demonstrate that the performance of the proposed algorithms (as measured by % GO term enrichment of subnetworks identified by the alignment) is competitive with some of the state-of-the-art algorithms for pair-wise alignment of large protein-protein interaction networks. Our results also show that the inter-species similarity scores computed based on graph kernels can be used to cluster the species into a species tree that is consistent with the known phylogenetic relationships among the species.

  3. Modeling, Analysis, Simulation, and Synthesis of Biomolecular Networks

    National Research Council Canada - National Science Library

    Ruben, Harvey; Kumar, Vijay; Sokolsky, Oleg

    2006-01-01

    ...) a first example of reachability analysis applied to a biomolecular system (lactose induction), 4) a model of tetracycline resistance that discriminates between two possible mechanisms for tetracycline diffusion through the cell membrane, and 5...

  4. Architecture of transcriptional regulatory circuits is knitted over the topology of bio-molecular interaction networks

    DEFF Research Database (Denmark)

    Soberano de Oliveira, Ana Paula; Patil, Kiran Raosaheb; Nielsen, Jens

    2008-01-01

    is to use the topology of bio-molecular interaction networks in order to constrain the solution space. Such approaches systematically integrate the existing biological knowledge with the 'omics' data. Results: Here we introduce a hypothesis-driven method that integrates bio-molecular network topology......Background: Uncovering the operating principles underlying cellular processes by using 'omics' data is often a difficult task due to the high-dimensionality of the solution space that spans all interactions among the bio-molecules under consideration. A rational way to overcome this problem...... with transcriptome data, thereby allowing the identification of key biological features (Reporter Features) around which transcriptional changes are significantly concentrated. We have combined transcriptome data with different biological networks in order to identify Reporter Gene Ontologies, Reporter Transcription...

  5. Formation of multiple networks

    DEFF Research Database (Denmark)

    Magnani, Matteo; Rossi, Luca

    2013-01-01

    we introduce the first network formation model for multiple networks. Network formation models are among the most popular tools in traditional network studies, because of both their practical and theoretical impact. However, existing models are not sufficient to describe the generation of multiple...

  6. The interplay of intrinsic and extrinsic bounded noises in biomolecular networks.

    Directory of Open Access Journals (Sweden)

    Giulio Caravagna

    Full Text Available After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a biomolecular network. The influence of intrinsic and extrinsic noises on biomolecular networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbations are clearly bounded. In this paper we consider Gillespie-like stochastic models of nonlinear networks, i.e. the intrinsic noise, where the model jump rates are affected by colored bounded extrinsic noises synthesized by a suitable biochemical state-dependent Langevin system. These systems are described by a master equation, and a simulation algorithm to analyze them is derived. This new modeling paradigm should enlarge the class of systems amenable at modeling. We investigated the influence of both amplitude and autocorrelation time of a extrinsic Sine-Wiener noise on: (i the Michaelis-Menten approximation of noisy enzymatic reactions, which we show to be applicable also in co-presence of both intrinsic and extrinsic noise, (ii a model of enzymatic futile cycle and (iii a genetic toggle switch. In (ii and (iii we show that the presence of a bounded extrinsic noise induces qualitative modifications in the probability densities of the involved chemicals, where new modes emerge, thus suggesting the possible functional role of bounded noises.

  7. The interplay of intrinsic and extrinsic bounded noises in biomolecular networks.

    Science.gov (United States)

    Caravagna, Giulio; Mauri, Giancarlo; d'Onofrio, Alberto

    2013-01-01

    After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a biomolecular network. The influence of intrinsic and extrinsic noises on biomolecular networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbations are clearly bounded. In this paper we consider Gillespie-like stochastic models of nonlinear networks, i.e. the intrinsic noise, where the model jump rates are affected by colored bounded extrinsic noises synthesized by a suitable biochemical state-dependent Langevin system. These systems are described by a master equation, and a simulation algorithm to analyze them is derived. This new modeling paradigm should enlarge the class of systems amenable at modeling. We investigated the influence of both amplitude and autocorrelation time of a extrinsic Sine-Wiener noise on: (i) the Michaelis-Menten approximation of noisy enzymatic reactions, which we show to be applicable also in co-presence of both intrinsic and extrinsic noise, (ii) a model of enzymatic futile cycle and (iii) a genetic toggle switch. In (ii) and (iii) we show that the presence of a bounded extrinsic noise induces qualitative modifications in the probability densities of the involved chemicals, where new modes emerge, thus suggesting the possible functional role of bounded noises.

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

    Science.gov (United States)

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

    2018-02-05

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

  9. Correlated Heterospectral Lipidomics for Biomolecular Profiling of Remyelination in Multiple Sclerosis

    Directory of Open Access Journals (Sweden)

    Mads S. Bergholt

    2017-12-01

    Full Text Available Analyzing lipid composition and distribution within the brain is important to study white matter pathologies that present focal demyelination lesions, such as multiple sclerosis. Some lesions can endogenously re-form myelin sheaths. Therapies aim to enhance this repair process in order to reduce neurodegeneration and disability progression in patients. In this context, a lipidomic analysis providing both precise molecular classification and well-defined localization is crucial to detect changes in myelin lipid content. Here we develop a correlated heterospectral lipidomic (HSL approach based on coregistered Raman spectroscopy, desorption electrospray ionization mass spectrometry (DESI-MS, and immunofluorescence imaging. We employ HSL to study the structural and compositional lipid profile of demyelination and remyelination in an induced focal demyelination mouse model and in multiple sclerosis lesions from patients ex vivo. Pixelwise coregistration of Raman spectroscopy and DESI-MS imaging generated a heterospectral map used to interrelate biomolecular structure and composition of myelin. Multivariate regression analysis enabled Raman-based assessment of highly specific lipid subtypes in complex tissue for the first time. This method revealed the temporal dynamics of remyelination and provided the first indication that newly formed myelin has a different lipid composition compared to normal myelin. HSL enables detailed molecular myelin characterization that can substantially improve upon the current understanding of remyelination in multiple sclerosis and provides a strategy to assess remyelination treatments in animal models.

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

    Science.gov (United States)

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

    2003-11-01

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

  11. A variational approach to moment-closure approximations for the kinetics of biomolecular reaction networks

    Science.gov (United States)

    Bronstein, Leo; Koeppl, Heinz

    2018-01-01

    Approximate solutions of the chemical master equation and the chemical Fokker-Planck equation are an important tool in the analysis of biomolecular reaction networks. Previous studies have highlighted a number of problems with the moment-closure approach used to obtain such approximations, calling it an ad hoc method. In this article, we give a new variational derivation of moment-closure equations which provides us with an intuitive understanding of their properties and failure modes and allows us to correct some of these problems. We use mixtures of product-Poisson distributions to obtain a flexible parametric family which solves the commonly observed problem of divergences at low system sizes. We also extend the recently introduced entropic matching approach to arbitrary ansatz distributions and Markov processes, demonstrating that it is a special case of variational moment closure. This provides us with a particularly principled approximation method. Finally, we extend the above approaches to cover the approximation of multi-time joint distributions, resulting in a viable alternative to process-level approximations which are often intractable.

  12. Multiple-Ring Digital Communication Network

    Science.gov (United States)

    Kirkham, Harold

    1992-01-01

    Optical-fiber digital communication network to support data-acquisition and control functions of electric-power-distribution networks. Optical-fiber links of communication network follow power-distribution routes. Since fiber crosses open power switches, communication network includes multiple interconnected loops with occasional spurs. At each intersection node is needed. Nodes of communication network include power-distribution substations and power-controlling units. In addition to serving data acquisition and control functions, each node acts as repeater, passing on messages to next node(s). Multiple-ring communication network operates on new AbNET protocol and features fiber-optic communication.

  13. Networks amid multiple logics

    DEFF Research Database (Denmark)

    Bergenholtz, Carsten; Bjerregaard, Toke

    The present study investigates how a high-tech-small-firm (HTSF) can carry out an inter-organizational search of actors located at universities. Responding to calls to study how firms navigate multiple institutional norms, this research examines the different strategies used by a HTSF to balance...... adopted academic norm-sets, commercial imperatives and formal regulations to support formation of networks and collaborations with universities. The findings show how the significance of weak and strong ties for the formation of collaborations and networks with universities is relative...

  14. iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D.

    Science.gov (United States)

    Liluashvili, Vaja; Kalayci, Selim; Fluder, Eugene; Wilson, Manda; Gabow, Aaron; Gümüs, Zeynep H

    2017-08-01

    Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field. © The Authors 2017. Published by Oxford University Press.

  15. A unified framework for unraveling the functional interaction structure of a biomolecular network based on stimulus-response experimental data.

    Science.gov (United States)

    Cho, Kwang-Hyun; Choo, Sang-Mok; Wellstead, Peter; Wolkenhauer, Olaf

    2005-08-15

    We propose a unified framework for the identification of functional interaction structures of biomolecular networks in a way that leads to a new experimental design procedure. In developing our approach, we have built upon previous work. Thus we begin by pointing out some of the restrictions associated with existing structure identification methods and point out how these restrictions may be eased. In particular, existing methods use specific forms of experimental algebraic equations with which to identify the functional interaction structure of a biomolecular network. In our work, we employ an extended form of these experimental algebraic equations which, while retaining their merits, also overcome some of their disadvantages. Experimental data are required in order to estimate the coefficients of the experimental algebraic equation set associated with the structure identification task. However, experimentalists are rarely provided with guidance on which parameters to perturb, and to what extent, to perturb them. When a model of network dynamics is required then there is also the vexed question of sample rate and sample time selection to be resolved. Supplying some answers to these questions is the main motivation of this paper. The approach is based on stationary and/or temporal data obtained from parameter perturbations, and unifies the previous approaches of Kholodenko et al. (PNAS 99 (2002) 12841-12846) and Sontag et al. (Bioinformatics 20 (2004) 1877-1886). By way of demonstration, we apply our unified approach to a network model which cannot be properly identified by existing methods. Finally, we propose an experiment design methodology, which is not limited by the amount of parameter perturbations, and illustrate its use with an in numero example.

  16. Scanning number and brightness yields absolute protein concentrations in live cells: a crucial parameter controlling functional bio-molecular interaction networks.

    Science.gov (United States)

    Papini, Christina; Royer, Catherine A

    2018-02-01

    Biological function results from properly timed bio-molecular interactions that transduce external or internal signals, resulting in any number of cellular fates, including triggering of cell-state transitions (division, differentiation, transformation, apoptosis), metabolic homeostasis and adjustment to changing physical or nutritional environments, amongst many more. These bio-molecular interactions can be modulated by chemical modifications of proteins, nucleic acids, lipids and other small molecules. They can result in bio-molecular transport from one cellular compartment to the other and often trigger specific enzyme activities involved in bio-molecular synthesis, modification or degradation. Clearly, a mechanistic understanding of any given high level biological function requires a quantitative characterization of the principal bio-molecular interactions involved and how these may change dynamically. Such information can be obtained using fluctation analysis, in particular scanning number and brightness, and used to build and test mechanistic models of the functional network to define which characteristics are the most important for its regulation.

  17. A model system for targeted drug release triggered by biomolecular signals logically processed through enzyme logic networks.

    Science.gov (United States)

    Mailloux, Shay; Halámek, Jan; Katz, Evgeny

    2014-03-07

    A new Sense-and-Act system was realized by the integration of a biocomputing system, performing analytical processes, with a signal-responsive electrode. A drug-mimicking release process was triggered by biomolecular signals processed by different logic networks, including three concatenated AND logic gates or a 3-input OR logic gate. Biocatalytically produced NADH, controlled by various combinations of input signals, was used to activate the electrochemical system. A biocatalytic electrode associated with signal-processing "biocomputing" systems was electrically connected to another electrode coated with a polymer film, which was dissolved upon the formation of negative potential releasing entrapped drug-mimicking species, an enzyme-antibody conjugate, operating as a model for targeted immune-delivery and consequent "prodrug" activation. The system offers great versatility for future applications in controlled drug release and personalized medicine.

  18. TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions

    Science.gov (United States)

    2017-01-01

    Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes. Availability: weilab.math.msu.edu/TDL/ PMID:28749969

  19. Protocol for multiple node network

    Science.gov (United States)

    Kirkham, Harold (Inventor)

    1995-01-01

    The invention is a multiple interconnected network of intelligent message-repeating remote nodes which employs an antibody recognition message termination process performed by all remote nodes and a remote node polling process performed by other nodes which are master units controlling remote nodes in respective zones of the network assigned to respective master nodes. Each remote node repeats only those messages originated in the local zone, to provide isolation among the master nodes.

  20. Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular networks

    NARCIS (Netherlands)

    R. Colak; F. Moser; J. Shu; A. Schönhuth (Alexander); N. Chen; M. Ester

    2010-01-01

    htmlabstractBackground Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not

  1. Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

    Directory of Open Access Journals (Sweden)

    Recep Colak

    2010-10-01

    Full Text Available Computational prediction of functionally related groups of genes (functional modules from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented.We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB, by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples.We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely

  2. Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

    Science.gov (United States)

    Colak, Recep; Moser, Flavia; Chu, Jeffrey Shih-Chieh; Schönhuth, Alexander; Chen, Nansheng; Ester, Martin

    2010-10-25

    Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense) regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB), by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely available large

  3. Concurrent conditional clustering of multiple networks: COCONETS.

    Directory of Open Access Journals (Sweden)

    Sabrina Kleessen

    Full Text Available The accumulation of high-throughput data from different experiments has facilitated the extraction of condition-specific networks over the same set of biological entities. Comparing and contrasting of such multiple biological networks is in the center of differential network biology, aiming at determining general and condition-specific responses captured in the network structure (i.e., included associations between the network components. We provide a novel way for comparison of multiple networks based on determining network clustering (i.e., partition into communities which is optimal across the set of networks with respect to a given cluster quality measure. To this end, we formulate the optimization-based problem of concurrent conditional clustering of multiple networks, termed COCONETS, based on the modularity. The solution to this problem is a clustering which depends on all considered networks and pinpoints their preserved substructures. We present theoretical results for special classes of networks to demonstrate the implications of conditionality captured by the COCONETS formulation. As the problem can be shown to be intractable, we extend an existing efficient greedy heuristic and applied it to determine concurrent conditional clusters on coexpression networks extracted from publically available time-resolved transcriptomics data of Escherichia coli under five stresses as well as on metabolite correlation networks from metabolomics data set from Arabidopsis thaliana exposed to eight environmental conditions. We demonstrate that the investigation of the differences between the clustering based on all networks with that obtained from a subset of networks can be used to quantify the specificity of biological responses. While a comparison of the Escherichia coli coexpression networks based on seminal properties does not pinpoint biologically relevant differences, the common network substructures extracted by COCONETS are supported by

  4. Multiple-Access Quantum-Classical Networks

    Science.gov (United States)

    Razavi, Mohsen

    2011-10-01

    A multi-user network that supports both classical and quantum communication is proposed. By relying on optical code-division multiple access techniques, this system offers simultaneous key exchange between multiple pairs of network users. A lower bound on the secure key generation rate will be derived for decoy-state quantum key distribution protocols.

  5. Biomolecular Science (Fact Sheet)

    Energy Technology Data Exchange (ETDEWEB)

    2012-04-01

    A brief fact sheet about NREL Photobiology and Biomolecular Science. The research goal of NREL's Biomolecular Science is to enable cost-competitive advanced lignocellulosic biofuels production by understanding the science critical for overcoming biomass recalcitrance and developing new product and product intermediate pathways. NREL's Photobiology focuses on understanding the capture of solar energy in photosynthetic systems and its use in converting carbon dioxide and water directly into hydrogen and advanced biofuels.

  6. Evaluation of Network Reliability for Computer Networks with Multiple Sources

    Directory of Open Access Journals (Sweden)

    Yi-Kuei Lin

    2012-01-01

    Full Text Available Evaluating the reliability of a network with multiple sources to multiple sinks is a critical issue from the perspective of quality management. Due to the unrealistic definition of paths of network models in previous literature, existing models are not appropriate for real-world computer networks such as the Taiwan Advanced Research and Education Network (TWAREN. This paper proposes a modified stochastic-flow network model to evaluate the network reliability of a practical computer network with multiple sources where data is transmitted through several light paths (LPs. Network reliability is defined as being the probability of delivering a specified amount of data from the sources to the sink. It is taken as a performance index to measure the service level of TWAREN. This paper studies the network reliability of the international portion of TWAREN from two sources (Taipei and Hsinchu to one sink (New York that goes through a submarine and land surface cable between Taiwan and the United States.

  7. Diversity Performance Analysis on Multiple HAP Networks

    Science.gov (United States)

    Dong, Feihong; Li, Min; Gong, Xiangwu; Li, Hongjun; Gao, Fengyue

    2015-01-01

    One of the main design challenges in wireless sensor networks (WSNs) is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP) is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO) techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO) model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV). In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) are derived. In addition, the average symbol error rate (ASER) with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI) and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques. PMID:26134102

  8. Diversity Performance Analysis on Multiple HAP Networks

    Directory of Open Access Journals (Sweden)

    Feihong Dong

    2015-06-01

    Full Text Available One of the main design challenges in wireless sensor networks (WSNs is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV. In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF and cumulative distribution function (CDF of the received signal-to-noise ratio (SNR are derived. In addition, the average symbol error rate (ASER with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques.

  9. Prediction of Biomolecular Complexes

    KAUST Repository

    Vangone, Anna

    2017-04-12

    Almost all processes in living organisms occur through specific interactions between biomolecules. Any dysfunction of those interactions can lead to pathological events. Understanding such interactions is therefore a crucial step in the investigation of biological systems and a starting point for drug design. In recent years, experimental studies have been devoted to unravel the principles of biomolecular interactions; however, due to experimental difficulties in solving the three-dimensional (3D) structure of biomolecular complexes, the number of available, high-resolution experimental 3D structures does not fulfill the current needs. Therefore, complementary computational approaches to model such interactions are necessary to assist experimentalists since a full understanding of how biomolecules interact (and consequently how they perform their function) only comes from 3D structures which provide crucial atomic details about binding and recognition processes. In this chapter we review approaches to predict biomolecular complexesBiomolecular complexes, introducing the concept of molecular dockingDocking, a technique which uses a combination of geometric, steric and energetics considerations to predict the 3D structure of a biological complex starting from the individual structures of its constituent parts. We provide a mini-guide about docking concepts, its potential and challenges, along with post-docking analysis and a list of related software.

  10. Prediction of Biomolecular Complexes

    KAUST Repository

    Vangone, Anna; Oliva, Romina; Cavallo, Luigi; Bonvin, Alexandre M. J. J.

    2017-01-01

    Almost all processes in living organisms occur through specific interactions between biomolecules. Any dysfunction of those interactions can lead to pathological events. Understanding such interactions is therefore a crucial step in the investigation of biological systems and a starting point for drug design. In recent years, experimental studies have been devoted to unravel the principles of biomolecular interactions; however, due to experimental difficulties in solving the three-dimensional (3D) structure of biomolecular complexes, the number of available, high-resolution experimental 3D structures does not fulfill the current needs. Therefore, complementary computational approaches to model such interactions are necessary to assist experimentalists since a full understanding of how biomolecules interact (and consequently how they perform their function) only comes from 3D structures which provide crucial atomic details about binding and recognition processes. In this chapter we review approaches to predict biomolecular complexesBiomolecular complexes, introducing the concept of molecular dockingDocking, a technique which uses a combination of geometric, steric and energetics considerations to predict the 3D structure of a biological complex starting from the individual structures of its constituent parts. We provide a mini-guide about docking concepts, its potential and challenges, along with post-docking analysis and a list of related software.

  11. Multiple network alignment on quantum computers

    Science.gov (United States)

    Daskin, Anmer; Grama, Ananth; Kais, Sabre

    2014-12-01

    Comparative analyses of graph-structured datasets underly diverse problems. Examples of these problems include identification of conserved functional components (biochemical interactions) across species, structural similarity of large biomolecules, and recurring patterns of interactions in social networks. A large class of such analyses methods quantify the topological similarity of nodes across networks. The resulting correspondence of nodes across networks, also called node alignment, can be used to identify invariant subgraphs across the input graphs. Given graphs as input, alignment algorithms use topological information to assign a similarity score to each -tuple of nodes, with elements (nodes) drawn from each of the input graphs. Nodes are considered similar if their neighbors are also similar. An alternate, equivalent view of these network alignment algorithms is to consider the Kronecker product of the input graphs and to identify high-ranked nodes in the Kronecker product graph. Conventional methods such as PageRank and HITS (Hypertext-Induced Topic Selection) can be used for this purpose. These methods typically require computation of the principal eigenvector of a suitably modified Kronecker product matrix of the input graphs. We adopt this alternate view of the problem to address the problem of multiple network alignment. Using the phase estimation algorithm, we show that the multiple network alignment problem can be efficiently solved on quantum computers. We characterize the accuracy and performance of our method and show that it can deliver exponential speedups over conventional (non-quantum) methods.

  12. Quantum key distribution network for multiple applications

    Science.gov (United States)

    Tajima, A.; Kondoh, T.; Ochi, T.; Fujiwara, M.; Yoshino, K.; Iizuka, H.; Sakamoto, T.; Tomita, A.; Shimamura, E.; Asami, S.; Sasaki, M.

    2017-09-01

    The fundamental architecture and functions of secure key management in a quantum key distribution (QKD) network with enhanced universal interfaces for smooth key sharing between arbitrary two nodes and enabling multiple secure communication applications are proposed. The proposed architecture consists of three layers: a quantum layer, key management layer and key supply layer. We explain the functions of each layer, the key formats in each layer and the key lifecycle for enabling a practical QKD network. A quantum key distribution-advanced encryption standard (QKD-AES) hybrid system and an encrypted smartphone system were developed as secure communication applications on our QKD network. The validity and usefulness of these systems were demonstrated on the Tokyo QKD Network testbed.

  13. Multiple routes transmitted epidemics on multiplex networks

    International Nuclear Information System (INIS)

    Zhao, Dawei; Li, Lixiang; Peng, Haipeng; Luo, Qun; Yang, Yixian

    2014-01-01

    This letter investigates the multiple routes transmitted epidemic process on multiplex networks. We propose detailed theoretical analysis that allows us to accurately calculate the epidemic threshold and outbreak size. It is found that the epidemic can spread across the multiplex network even if all the network layers are well below their respective epidemic thresholds. Strong positive degree–degree correlation of nodes in multiplex network could lead to a much lower epidemic threshold and a relatively smaller outbreak size. However, the average similarity of neighbors from different layers of nodes has no obvious effect on the epidemic threshold and outbreak size. -- Highlights: •We studies multiple routes transmitted epidemic process on multiplex networks. •SIR model and bond percolation theory are used to analyze the epidemic processes. •We derive equations to accurately calculate the epidemic threshold and outbreak size. •ASN has no effect on the epidemic threshold and outbreak size. •Strong positive DDC leads to a lower epidemic threshold and a smaller outbreak size.

  14. Multiple routes transmitted epidemics on multiplex networks

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Dawei [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China); National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China); Shandong Provincial Key Laboratory of Computer Network, Shandong Computer Science Center, Jinan 250014 (China); Li, Lixiang [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China); National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China); Peng, Haipeng, E-mail: penghaipeng@bupt.edu.cn [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China); National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China); Luo, Qun; Yang, Yixian [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China); National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China)

    2014-02-01

    This letter investigates the multiple routes transmitted epidemic process on multiplex networks. We propose detailed theoretical analysis that allows us to accurately calculate the epidemic threshold and outbreak size. It is found that the epidemic can spread across the multiplex network even if all the network layers are well below their respective epidemic thresholds. Strong positive degree–degree correlation of nodes in multiplex network could lead to a much lower epidemic threshold and a relatively smaller outbreak size. However, the average similarity of neighbors from different layers of nodes has no obvious effect on the epidemic threshold and outbreak size. -- Highlights: •We studies multiple routes transmitted epidemic process on multiplex networks. •SIR model and bond percolation theory are used to analyze the epidemic processes. •We derive equations to accurately calculate the epidemic threshold and outbreak size. •ASN has no effect on the epidemic threshold and outbreak size. •Strong positive DDC leads to a lower epidemic threshold and a smaller outbreak size.

  15. Programming in biomolecular computation

    DEFF Research Database (Denmark)

    Hartmann, Lars Røeboe; Jones, Neil; Simonsen, Jakob Grue

    2011-01-01

    Our goal is to provide a top-down approach to biomolecular computation. In spite of widespread discussion about connections between biology and computation, one question seems notable by its absence: Where are the programs? We identify a number of common features in programming that seem...... conspicuously absent from the literature on biomolecular computing; to partially redress this absence, we introduce a model of computation that is evidently programmable, by programs reminiscent of low-level computer machine code; and at the same time biologically plausible: its functioning is defined...... by a single and relatively small set of chemical-like reaction rules. Further properties: the model is stored-program: programs are the same as data, so programs are not only executable, but are also compilable and interpretable. It is universal: all computable functions can be computed (in natural ways...

  16. Effects of multiple spreaders in community networks

    Science.gov (United States)

    Hu, Zhao-Long; Ren, Zhuo-Ming; Yang, Guang-Yong; Liu, Jian-Guo

    2014-12-01

    Human contact networks exhibit the community structure. Understanding how such community structure affects the epidemic spreading could provide insights for preventing the spreading of epidemics between communities. In this paper, we explore the spreading of multiple spreaders in community networks. A network based on the clustering preferential mechanism is evolved, whose communities are detected by the Girvan-Newman (GN) algorithm. We investigate the spreading effectiveness by selecting the nodes as spreaders in the following ways: nodes with the largest degree in each community (community hubs), the same number of nodes with the largest degree from the global network (global large-degree) and randomly selected one node within each community (community random). The experimental results on the SIR model show that the spreading effectiveness based on the global large-degree and community hubs methods is the same in the early stage of the infection and the method of community random is the worst. However, when the infection rate exceeds the critical value, the global large-degree method embodies the worst spreading effectiveness. Furthermore, the discrepancy of effectiveness for the three methods will decrease as the infection rate increases. Therefore, we should immunize the hubs in each community rather than those hubs in the global network to prevent the outbreak of epidemics.

  17. Biomolecular Sciences: uniting Biology and Chemistry

    NARCIS (Netherlands)

    Vrieling, Engel

    2017-01-01

    Biomolecular Sciences: uniting Biology and Chemistry www.rug.nl/research/gbb The scientific discoveries in biomolecular sciences have benefitted enormously from technological innovations. At the Groningen Biomolecular Science and Biotechnology Institute (GBB) we now sequence a genome in days,

  18. Biomolecular logic systems: applications to biosensors and bioactuators

    Science.gov (United States)

    Katz, Evgeny

    2014-05-01

    The paper presents an overview of recent advances in biosensors and bioactuators based on the biocomputing concept. Novel biosensors digitally process multiple biochemical signals through Boolean logic networks of coupled biomolecular reactions and produce output in the form of YES/NO response. Compared to traditional single-analyte sensing devices, biocomputing approach enables a high-fidelity multi-analyte biosensing, particularly beneficial for biomedical applications. Multi-signal digital biosensors thus promise advances in rapid diagnosis and treatment of diseases by processing complex patterns of physiological biomarkers. Specifically, they can provide timely detection and alert to medical emergencies, along with an immediate therapeutic intervention. Application of the biocomputing concept has been successfully demonstrated for systems performing logic analysis of biomarkers corresponding to different injuries, particularly exemplified for liver injury. Wide-ranging applications of multi-analyte digital biosensors in medicine, environmental monitoring and homeland security are anticipated. "Smart" bioactuators, for example for signal-triggered drug release, were designed by interfacing switchable electrodes and biocomputing systems. Integration of novel biosensing and bioactuating systems with the biomolecular information processing systems keeps promise for further scientific advances and numerous practical applications.

  19. Role of biomolecular logic systems in biosensors and bioactuators

    Science.gov (United States)

    Mailloux, Shay; Katz, Evgeny

    2014-09-01

    An overview of recent advances in biosensors and bioactuators based on biocomputing systems is presented. Biosensors digitally process multiple biochemical signals through Boolean logic networks of coupled biomolecular reactions and produce an output in the form of a YES/NO response. Compared to traditional single-analyte sensing devices, the biocomputing approach enables high-fidelity multianalyte biosensing, which is particularly beneficial for biomedical applications. Multisignal digital biosensors thus promise advances in rapid diagnosis and treatment of diseases by processing complex patterns of physiological biomarkers. Specifically, they can provide timely detection and alert medical personnel of medical emergencies together with immediate therapeutic intervention. Application of the biocomputing concept has been successfully demonstrated for systems performing logic analysis of biomarkers corresponding to different injuries, particularly as exemplified for liver injury. Wide-ranging applications of multianalyte digital biosensors in medicine, environmental monitoring, and homeland security are anticipated. "Smart" bioactuators, for signal-triggered drug release, for example, were designed by interfacing switchable electrodes with biocomputing systems. Integration of biosensing and bioactuating systems with biomolecular information processing systems advances the potential for further scientific innovations and various practical applications.

  20. Synchronization in networks with multiple interaction layers

    Science.gov (United States)

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

    2016-01-01

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

  1. Biomolecular modelling and simulations

    CERN Document Server

    Karabencheva-Christova, Tatyana

    2014-01-01

    Published continuously since 1944, the Advances in Protein Chemistry and Structural Biology series is the essential resource for protein chemists. Each volume brings forth new information about protocols and analysis of proteins. Each thematically organized volume is guest edited by leading experts in a broad range of protein-related topics. Describes advances in biomolecular modelling and simulations Chapters are written by authorities in their field Targeted to a wide audience of researchers, specialists, and students The information provided in the volume is well supported by a number of high quality illustrations, figures, and tables.

  2. Membrane-based biomolecular smart materials

    International Nuclear Information System (INIS)

    Sarles, Stephen A; Leo, Donald J

    2011-01-01

    Membrane-based biomolecular materials are a new class of smart material that feature networks of artificial lipid bilayers contained within durable synthetic substrates. Bilayers contained within this modular material platform provide an environment that can be tailored to host an enormous diversity of functional biomolecules, where the functionality of the global material system depends on the type(s) and organization(s) of the biomolecules that are chosen. In this paper, we review a series of biomolecular material platforms developed recently within the Leo Group at Virginia Tech and we discuss several novel coupling mechanisms provided by these hybrid material systems. The platforms developed demonstrate that the functions of biomolecules and the properties of synthetic materials can be combined to operate in concert, and the examples provided demonstrate how the formation and properties of a lipid bilayer can respond to a variety of stimuli including mechanical forces and electric fields

  3. Biomolecular EPR spectroscopy

    CERN Document Server

    Hagen, Wilfred Raymond

    2008-01-01

    Comprehensive, Up-to-Date Coverage of Spectroscopy Theory and its Applications to Biological SystemsAlthough a multitude of books have been published about spectroscopy, most of them only occasionally refer to biological systems and the specific problems of biomolecular EPR (bioEPR). Biomolecular EPR Spectroscopy provides a practical introduction to bioEPR and demonstrates how this remarkable tool allows researchers to delve into the structural, functional, and analytical analysis of paramagnetic molecules found in the biochemistry of all species on the planet. A Must-Have Reference in an Intrinsically Multidisciplinary FieldThis authoritative reference seamlessly covers all important bioEPR applications, including low-spin and high-spin metalloproteins, spin traps and spin lables, interaction between active sites, and redox systems. It is loaded with practical tricks as well as do's and don'ts that are based on the author's 30 years of experience in the field. The book also comes with an unprecedented set of...

  4. Multiple network interface core apparatus and method

    Science.gov (United States)

    Underwood, Keith D [Albuquerque, NM; Hemmert, Karl Scott [Albuquerque, NM

    2011-04-26

    A network interface controller and network interface control method comprising providing a single integrated circuit as a network interface controller and employing a plurality of network interface cores on the single integrated circuit.

  5. Multiple Social Networks, Data Models and Measures for

    DEFF Research Database (Denmark)

    Magnani, Matteo; Rossi, Luca

    2017-01-01

    Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one...

  6. Robustness Analysis of Real Network Topologies Under Multiple Failure Scenarios

    DEFF Research Database (Denmark)

    Manzano, M.; Marzo, J. L.; Calle, E.

    2012-01-01

    on topological characteristics. Recently approaches also consider the services supported by such networks. In this paper we carry out a robustness analysis of five real backbone telecommunication networks under defined multiple failure scenarios, taking into account the consequences of the loss of established......Nowadays the ubiquity of telecommunication networks, which underpin and fulfill key aspects of modern day living, is taken for granted. Significant large-scale failures have occurred in the last years affecting telecommunication networks. Traditionally, network robustness analysis has been focused...... connections. Results show which networks are more robust in response to a specific type of failure....

  7. Efficient Cancer Detection Using Multiple Neural Networks.

    Science.gov (United States)

    Shell, John; Gregory, William D

    2017-01-01

    The inspection of live excised tissue specimens to ascertain malignancy is a challenging task in dermatopathology and generally in histopathology. We introduce a portable desktop prototype device that provides highly accurate neural network classification of malignant and benign tissue. The handheld device collects 47 impedance data samples from 1 Hz to 32 MHz via tetrapolar blackened platinum electrodes. The data analysis was implemented with six different backpropagation neural networks (BNN). A data set consisting of 180 malignant and 180 benign breast tissue data files in an approved IRB study at the Aurora Medical Center, Milwaukee, WI, USA, were utilized as a neural network input. The BNN structure consisted of a multi-tiered consensus approach autonomously selecting four of six neural networks to determine a malignant or benign classification. The BNN analysis was then compared with the histology results with consistent sensitivity of 100% and a specificity of 100%. This implementation successfully relied solely on statistical variation between the benign and malignant impedance data and intricate neural network configuration. This device and BNN implementation provides a novel approach that could be a valuable tool to augment current medical practice assessment of the health of breast, squamous, and basal cell carcinoma and other excised tissue without requisite tissue specimen expertise. It has the potential to provide clinical management personnel with a fast non-invasive accurate assessment of biopsied or sectioned excised tissue in various clinical settings.

  8. Optical Multiple Access Network (OMAN) for advanced processing satellite applications

    Science.gov (United States)

    Mendez, Antonio J.; Gagliardi, Robert M.; Park, Eugene; Ivancic, William D.; Sherman, Bradley D.

    1991-01-01

    An OMAN breadboard for exploring advanced processing satellite circuit switch applications is introduced. Network architecture, hardware trade offs, and multiple user interference issues are presented. The breadboard test set up and experimental results are discussed.

  9. Multiple leakage localization and leak size estimation in water networks

    NARCIS (Netherlands)

    Abbasi, N.; Habibi, H.; Hurkens, C.A.J.; Klabbers, M.D.; Tijsseling, A.S.; Eijndhoven, van S.J.L.

    2012-01-01

    Water distribution networks experience considerable losses due to leakage, often at multiple locations simultaneously. Leakage detection and localization based on sensor placement and online pressure monitoring could be fast and economical. Using the difference between estimated and measured

  10. Radio Access Sharing Strategies for Multiple Operators in Cellular Networks

    DEFF Research Database (Denmark)

    Popovska Avramova, Andrijana; Iversen, Villy Bæk

    2015-01-01

    deployments (required for coverage enhancement), increased base station utilization, and reduced overall power consumption. Today, network sharing in the radio access part is passive and limited to cell sites. With the introduction of Cloud Radio Access Network and Software Defined Networking adoption...... to the radio access network, the possibility for sharing baseband processing and radio spectrum becomes an important aspect of network sharing. This paper investigates strategies for active sharing of radio access among multiple operators, and analyses the individual benefits depending on the sharing degree...

  11. Smartphones for cell and biomolecular detection.

    Science.gov (United States)

    Liu, Xiyuan; Lin, Tung-Yi; Lillehoj, Peter B

    2014-11-01

    Recent advances in biomedical science and technology have played a significant role in the development of new sensors and assays for cell and biomolecular detection. Generally, these efforts are aimed at reducing the complexity and costs associated with diagnostic testing so that it can be performed outside of a laboratory or hospital setting, requiring minimal equipment and user involvement. In particular, point-of-care (POC) testing offers immense potential for many important applications including medical diagnosis, environmental monitoring, food safety, and biosecurity. When coupled with smartphones, POC systems can offer portability, ease of use and enhanced functionality while maintaining performance. This review article focuses on recent advancements and developments in smartphone-based POC systems within the last 6 years with an emphasis on cell and biomolecular detection. These devices typically comprise multiple components, such as detectors, sample processors, disposable chips, batteries, and software, which are integrated with a commercial smartphone. One of the most important aspects of developing these systems is the integration of these components onto a compact and lightweight platform that requires minimal power. Researchers have demonstrated several promising approaches employing various detection schemes and device configurations, and it is expected that further developments in biosensors, battery technology and miniaturized electronics will enable smartphone-based POC technologies to become more mainstream tools in the scientific and biomedical communities.

  12. Sexual networks and social capital: multiple and concurrent sexual ...

    African Journals Online (AJOL)

    Multiple and concurrent sexual partnerships (MCP) are prevalent in southern Africa and have been identified as a primary cause of high HIV prevalence in this region. Sexual liaisons with multiple partners serve to increase the size and diversity of an individual's sexual — and social — network and therefore to increase their ...

  13. Innovation in Multiple Networks and Networks of Networks: The Case of the Fruit Sector in Emilia‐Romagna

    Directory of Open Access Journals (Sweden)

    Davide Viaggi

    2013-02-01

    Full Text Available In the paper we examine the issue of food systems in which farms participate in multiple networks that, for their part, tend also to be members of networks of networks. The issue is addressed through a descriptive analysis of the fruit sector in Emilia‐Romagna (Italy. The farms in the area tend to join a different network for each product/product type. Innovation networks are embedded in commercialization or input provider networks, but separate (parallel networks also exist, particularly for basic research activities. Networks of networks are largely a product of the cooperative system. The paper concludes by emphasising the need for further research in multiple networking strategies and the connection betweencommercialisation networks and innovation.

  14. Infinite Multiple Membership Relational Modeling for Complex Networks

    DEFF Research Database (Denmark)

    Mørup, Morten; Schmidt, Mikkel Nørgaard; Hansen, Lars Kai

    Learning latent structure in complex networks has become an important problem fueled by many types of networked data originating from practically all fields of science. In this paper, we propose a new non-parametric Bayesian multiplemembership latent feature model for networks. Contrary to existing...... multiplemembership models that scale quadratically in the number of vertices the proposedmodel scales linearly in the number of links admittingmultiple-membership analysis in large scale networks. We demonstrate a connection between the single membership relational model and multiple membership models and show...

  15. Multiplicative Attribute Graph Model of Real-World Networks

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Myunghwan [Stanford Univ., CA (United States); Leskovec, Jure [Stanford Univ., CA (United States)

    2010-10-20

    Large scale real-world network data, such as social networks, Internet andWeb graphs, is ubiquitous in a variety of scientific domains. The study of such social and information networks commonly finds patterns and explain their emergence through tractable models. In most networks, especially in social networks, nodes also have a rich set of attributes (e.g., age, gender) associatedwith them. However, most of the existing network models focus only on modeling the network structure while ignoring the features of nodes in the network. Here we present a class of network models that we refer to as the Multiplicative Attribute Graphs (MAG), which naturally captures the interactions between the network structure and node attributes. We consider a model where each node has a vector of categorical features associated with it. The probability of an edge between a pair of nodes then depends on the product of individual attributeattribute similarities. The model yields itself to mathematical analysis as well as fit to real data. We derive thresholds for the connectivity, the emergence of the giant connected component, and show that the model gives rise to graphs with a constant diameter. Moreover, we analyze the degree distribution to show that the model can produce networks with either lognormal or power-law degree distribution depending on certain conditions.

  16. Predicting Protein Function via Semantic Integration of Multiple Networks.

    Science.gov (United States)

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

    2016-01-01

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

  17. Multiple k Nearest Neighbor Query Processing in Spatial Network Databases

    DEFF Research Database (Denmark)

    Xuegang, Huang; Jensen, Christian Søndergaard; Saltenis, Simonas

    2006-01-01

    This paper concerns the efficient processing of multiple k nearest neighbor queries in a road-network setting. The assumed setting covers a range of scenarios such as the one where a large population of mobile service users that are constrained to a road network issue nearest-neighbor queries...... for points of interest that are accessible via the road network. Given multiple k nearest neighbor queries, the paper proposes progressive techniques that selectively cache query results in main memory and subsequently reuse these for query processing. The paper initially proposes techniques for the case...... where an upper bound on k is known a priori and then extends the techniques to the case where this is not so. Based on empirical studies with real-world data, the paper offers insight into the circumstances under which the different proposed techniques can be used with advantage for multiple k nearest...

  18. Multiple-predators-based capture process on complex networks

    International Nuclear Information System (INIS)

    Sharafat, Rajput Ramiz; Pu Cunlai; Li Jie; Chen Rongbin; Xu Zhongqi

    2017-01-01

    The predator/prey (capture) problem is a prototype of many network-related applications. We study the capture process on complex networks by considering multiple predators from multiple sources. In our model, some lions start from multiple sources simultaneously to capture the lamb by biased random walks, which are controlled with a free parameter α . We derive the distribution of the lamb’s lifetime and the expected lifetime 〈 T 〉. Through simulation, we find that the expected lifetime drops substantially with the increasing number of lions. Moreover, we study how the underlying topological structure affects the capture process, and obtain that locating on small-degree nodes is better than on large-degree nodes to prolong the lifetime of the lamb. The dense or homogeneous network structures are against the survival of the lamb. We also discuss how to improve the capture efficiency in our model. (paper)

  19. Efficient Routing in Wireless Sensor Networks with Multiple Sessions

    OpenAIRE

    Dianjie Lu; Guijuan Zhang; Ren Han; Xiangwei Zheng; Hong Liu

    2014-01-01

    Wireless Sensor Networks (WSNs) are subject to node failures because of limited energy and link unreliability which makes the design of routing protocols in such networks a challenging task. The multipath routing scheme is an optimal alternative to address this problem which splits the traffic across multiple paths instead of routing all the traffic along a single path. However, using more paths introduces more contentions which degrade energy efficiency. The problem becomes even more difficu...

  20. AC Power Local Network with Multiple Power Routers

    Directory of Open Access Journals (Sweden)

    Ryo Takahashi

    2013-12-01

    Full Text Available Controlling power flow and achieving appropriate matching between power sources and loads according to the quality of energy is expected to be one of the approaches to reduce wasted energy consumption. A power router, proposed recently, has the capability of realizing circuit switching in a power distribution network. This study focuses on the feasibility of an AC power routing network system composed of multiple power routers. To evaluate the feasibility, we experimentally confirm the circuit switching operation of the parallel and series configurations of the power routers, so that the network system can be designed by the combination of parallel and series configurations.

  1. Optically transparent multiple access networks employing incoherent spectral codes

    NARCIS (Netherlands)

    Huiszoon, B.

    2008-01-01

    This Ph.D. thesis is divided into 7 chapters to provide the reader an overview of the main results achieved in di®erent sub-topics of the study towards optically transparent multiple access networks employing incoherent spectral codes taking into account wireless transmission aspects. The work

  2. Perfect quantum multiple-unicast network coding protocol

    Science.gov (United States)

    Li, Dan-Dan; Gao, Fei; Qin, Su-Juan; Wen, Qiao-Yan

    2018-01-01

    In order to realize long-distance and large-scale quantum communication, it is natural to utilize quantum repeater. For a general quantum multiple-unicast network, it is still puzzling how to complete communication tasks perfectly with less resources such as registers. In this paper, we solve this problem. By applying quantum repeaters to multiple-unicast communication problem, we give encoding-decoding schemes for source nodes, internal ones and target ones, respectively. Source-target nodes share EPR pairs by using our encoding-decoding schemes over quantum multiple-unicast network. Furthermore, quantum communication can be accomplished perfectly via teleportation. Compared with existed schemes, our schemes can reduce resource consumption and realize long-distance transmission of quantum information.

  3. Whitelists Based Multiple Filtering Techniques in SCADA Sensor Networks

    Directory of Open Access Journals (Sweden)

    DongHo Kang

    2014-01-01

    Full Text Available Internet of Things (IoT consists of several tiny devices connected together to form a collaborative computing environment. Recently IoT technologies begin to merge with supervisory control and data acquisition (SCADA sensor networks to more efficiently gather and analyze real-time data from sensors in industrial environments. But SCADA sensor networks are becoming more and more vulnerable to cyber-attacks due to increased connectivity. To safely adopt IoT technologies in the SCADA environments, it is important to improve the security of SCADA sensor networks. In this paper we propose a multiple filtering technique based on whitelists to detect illegitimate packets. Our proposed system detects the traffic of network and application protocol attacks with a set of whitelists collected from normal traffic.

  4. Tools and Models for Integrating Multiple Cellular Networks

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-11-06

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

  5. Integrative NMR for biomolecular research

    International Nuclear Information System (INIS)

    Lee, Woonghee; Cornilescu, Gabriel; Dashti, Hesam; Eghbalnia, Hamid R.; Tonelli, Marco; Westler, William M.; Butcher, Samuel E.; Henzler-Wildman, Katherine A.; Markley, John L.

    2016-01-01

    NMR spectroscopy is a powerful technique for determining structural and functional features of biomolecules in physiological solution as well as for observing their intermolecular interactions in real-time. However, complex steps associated with its practice have made the approach daunting for non-specialists. We introduce an NMR platform that makes biomolecular NMR spectroscopy much more accessible by integrating tools, databases, web services, and video tutorials that can be launched by simple installation of NMRFAM software packages or using a cross-platform virtual machine that can be run on any standard laptop or desktop computer. The software package can be downloaded freely from the NMRFAM software download page ( http://pine.nmrfam.wisc.edu/download-packages.html http://pine.nmrfam.wisc.edu/download_packages.html ), and detailed instructions are available from the Integrative NMR Video Tutorial page ( http://pine.nmrfam.wisc.edu/integrative.html http://pine.nmrfam.wisc.edu/integrative.html ).

  6. Integrative NMR for biomolecular research

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Woonghee, E-mail: whlee@nmrfam.wisc.edu; Cornilescu, Gabriel; Dashti, Hesam; Eghbalnia, Hamid R.; Tonelli, Marco; Westler, William M.; Butcher, Samuel E.; Henzler-Wildman, Katherine A.; Markley, John L., E-mail: markley@nmrfam.wisc.edu [University of Wisconsin-Madison, National Magnetic Resonance Facility at Madison and Biochemistry Department (United States)

    2016-04-15

    NMR spectroscopy is a powerful technique for determining structural and functional features of biomolecules in physiological solution as well as for observing their intermolecular interactions in real-time. However, complex steps associated with its practice have made the approach daunting for non-specialists. We introduce an NMR platform that makes biomolecular NMR spectroscopy much more accessible by integrating tools, databases, web services, and video tutorials that can be launched by simple installation of NMRFAM software packages or using a cross-platform virtual machine that can be run on any standard laptop or desktop computer. The software package can be downloaded freely from the NMRFAM software download page ( http://pine.nmrfam.wisc.edu/download-packages.html http://pine.nmrfam.wisc.edu/download{sub p}ackages.html ), and detailed instructions are available from the Integrative NMR Video Tutorial page ( http://pine.nmrfam.wisc.edu/integrative.html http://pine.nmrfam.wisc.edu/integrative.html ).

  7. Computing all hybridization networks for multiple binary phylogenetic input trees.

    Science.gov (United States)

    Albrecht, Benjamin

    2015-07-30

    The computation of phylogenetic trees on the same set of species that are based on different orthologous genes can lead to incongruent trees. One possible explanation for this behavior are interspecific hybridization events recombining genes of different species. An important approach to analyze such events is the computation of hybridization networks. This work presents the first algorithm computing the hybridization number as well as a set of representative hybridization networks for multiple binary phylogenetic input trees on the same set of taxa. To improve its practical runtime, we show how this algorithm can be parallelized. Moreover, we demonstrate the efficiency of the software Hybroscale, containing an implementation of our algorithm, by comparing it to PIRNv2.0, which is so far the best available software computing the exact hybridization number for multiple binary phylogenetic trees on the same set of taxa. The algorithm is part of the software Hybroscale, which was developed specifically for the investigation of hybridization networks including their computation and visualization. Hybroscale is freely available(1) and runs on all three major operating systems. Our simulation study indicates that our approach is on average 100 times faster than PIRNv2.0. Moreover, we show how Hybroscale improves the interpretation of the reported hybridization networks by adding certain features to its graphical representation.

  8. Cooperative and Adaptive Network Coding for Gradient Based Routing in Wireless Sensor Networks with Multiple Sinks

    Directory of Open Access Journals (Sweden)

    M. E. Migabo

    2017-01-01

    Full Text Available Despite its low computational cost, the Gradient Based Routing (GBR broadcast of interest messages in Wireless Sensor Networks (WSNs causes significant packets duplications and unnecessary packets transmissions. This results in energy wastage, traffic load imbalance, high network traffic, and low throughput. Thanks to the emergence of fast and powerful processors, the development of efficient network coding strategies is expected to enable efficient packets aggregations and reduce packets retransmissions. For multiple sinks WSNs, the challenge consists of efficiently selecting a suitable network coding scheme. This article proposes a Cooperative and Adaptive Network Coding for GBR (CoAdNC-GBR technique which considers the network density as dynamically defined by the average number of neighbouring nodes, to efficiently aggregate interest messages. The aggregation is performed by means of linear combinations of random coefficients of a finite Galois Field of variable size GF(2S at each node and the decoding is performed by means of Gaussian elimination. The obtained results reveal that, by exploiting the cooperation of the multiple sinks, the CoAdNC-GBR not only improves the transmission reliability of links and lowers the number of transmissions and the propagation latency, but also enhances the energy efficiency of the network when compared to the GBR-network coding (GBR-NC techniques.

  9. 3D Filament Network Segmentation with Multiple Active Contours

    Science.gov (United States)

    Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

    2014-03-01

    Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and microtubules. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we developed a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D TIRF Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy.

  10. Motor network efficiency and disability in multiple sclerosis

    Science.gov (United States)

    Yaldizli, Özgür; Sethi, Varun; Muhlert, Nils; Liu, Zheng; Samson, Rebecca S.; Altmann, Daniel R.; Ron, Maria A.; Wheeler-Kingshott, Claudia A.M.; Miller, David H.; Chard, Declan T.

    2015-01-01

    Objective: To develop a composite MRI-based measure of motor network integrity, and determine if it explains disability better than conventional MRI measures in patients with multiple sclerosis (MS). Methods: Tract density imaging and constrained spherical deconvolution tractography were used to identify motor network connections in 22 controls. Fractional anisotropy (FA), magnetization transfer ratio (MTR), and normalized volume were computed in each tract in 71 people with relapse onset MS. Principal component analysis was used to distill the FA, MTR, and tract volume data into a single metric for each tract, which in turn was used to compute a composite measure of motor network efficiency (composite NE) using graph theory. Associations were investigated between the Expanded Disability Status Scale (EDSS) and the following MRI measures: composite motor NE, NE calculated using FA alone, FA averaged in the combined motor network tracts, brain T2 lesion volume, brain parenchymal fraction, normal-appearing white matter MTR, and cervical cord cross-sectional area. Results: In univariable analysis, composite motor NE explained 58% of the variation in EDSS in the whole MS group, more than twice that of the other MRI measures investigated. In a multivariable regression model, only composite NE and disease duration were independently associated with EDSS. Conclusions: A composite MRI measure of motor NE was able to predict disability substantially better than conventional non-network-based MRI measures. PMID:26320199

  11. Construction of Individual Morphological Brain Networks with Multiple Morphometric Features

    Directory of Open Access Journals (Sweden)

    Chunlan Yang

    2017-04-01

    Full Text Available In recent years, researchers have increased attentions to the morphological brain network, which is generally constructed by measuring the mathematical correlation across regions using a certain morphometric feature, such as regional cortical thickness and voxel intensity. However, cerebral structure can be characterized by various factors, such as regional volume, surface area, and curvature. Moreover, most of the morphological brain networks are population-based, which has limitations in the investigations of individual difference and clinical applications. Hence, we have extended previous studies by proposing a novel method for realizing the construction of an individual-based morphological brain network through a combination of multiple morphometric features. In particular, interregional connections are estimated using our newly introduced feature vectors, namely, the Pearson correlation coefficient of the concatenation of seven morphometric features. Experiments were performed on a healthy cohort of 55 subjects (24 males aged from 20 to 29 and 31 females aged from 20 to 28 each scanned twice, and reproducibility was evaluated through test–retest reliability. The robustness of morphometric features was measured firstly to select the more reproducible features to form the connectomes. Then the topological properties were analyzed and compared with previous reports of different modalities. Small-worldness was observed in all the subjects at the range of the entire network sparsity (20–40%, and configurations were comparable with previous findings at the sparsity of 23%. The spatial distributions of the hub were found to be significantly influenced by the individual variances, and the hubs obtained by averaging across subjects and sparsities showed correspondence with previous reports. The intraclass coefficient of graphic properties (clustering coefficient = 0.83, characteristic path length = 0.81, betweenness centrality = 0.78 indicates

  12. Conducting polymer based biomolecular electronic devices

    Indian Academy of Sciences (India)

    Conducting polymers; LB films; biosensor microactuators; monolayers. ... have been projected for applications for a wide range of biomolecular electronic devices such as optical, electronic, drug-delivery, memory and biosensing devices.

  13. Biomolecular transport and separation in nanotubular networks.

    Energy Technology Data Exchange (ETDEWEB)

    Stachowiak, Jeanne C.; Stevens, Mark Jackson (Sandia National Laboratories, Albuquerque, NM); Robinson, David B.; Branda, Steven S.; Zendejas, Frank; Meagher, Robert J.; Sasaki, Darryl Yoshio; Bachand, George David (Sandia National Laboratories, Albuquerque, NM); Hayden, Carl C.; Sinha, Anupama; Abate, Elisa; Wang, Julia; Carroll-Portillo, Amanda (Sandia National Laboratories, Albuquerque, NM); Liu, Haiqing (Sandia National Laboratories, Albuquerque, NM)

    2010-09-01

    Cell membranes are dynamic substrates that achieve a diverse array of functions through multi-scale reconfigurations. We explore the morphological changes that occur upon protein interaction to model membrane systems that induce deformation of their planar structure to yield nanotube assemblies. In the two examples shown in this report we will describe the use of membrane adhesion and particle trajectory to form lipid nanotubes via mechanical stretching, and protein adsorption onto domains and the induction of membrane curvature through steric pressure. Through this work the relationship between membrane bending rigidity, protein affinity, and line tension of phase separated structures were examined and their relationship in biological membranes explored.

  14. Downlink Non-Orthogonal Multiple Access (NOMA) in Poisson Networks

    KAUST Repository

    Ali, Konpal S.

    2018-03-21

    A network model is considered where Poisson distributed base stations transmit to $N$ power-domain non-orthogonal multiple access (NOMA) users (UEs) each that employ successive interference cancellation (SIC) for decoding. We propose three models for the clustering of NOMA UEs and consider two different ordering techniques for the NOMA UEs: mean signal power-based and instantaneous signal-to-intercell-interference-and-noise-ratio-based. For each technique, we present a signal-to-interference-and-noise ratio analysis for the coverage of the typical UE. We plot the rate region for the two-user case and show that neither ordering technique is consistently superior to the other. We propose two efficient algorithms for finding a feasible resource allocation that maximize the cell sum rate $\\\\mathcal{R}_{\\ m tot}$, for general $N$, constrained to: 1) a minimum rate $\\\\mathcal{T}$ for each UE, 2) identical rates for all UEs. We show the existence of: 1) an optimum $N$ that maximizes the constrained $\\\\mathcal{R}_{\\ m tot}$ given a set of network parameters, 2) a critical SIC level necessary for NOMA to outperform orthogonal multiple access. The results highlight the importance in choosing the network parameters $N$, the constraints, and the ordering technique to balance the $\\\\mathcal{R}_{\\ m tot}$ and fairness requirements. We also show that interference-aware UE clustering can significantly improve performance.

  15. Non-Orthogonal Multiple Access for Ubiquitous Wireless Sensor Networks.

    Science.gov (United States)

    Anwar, Asim; Seet, Boon-Chong; Ding, Zhiguo

    2018-02-08

    Ubiquitous wireless sensor networks (UWSNs) have become a critical technology for enabling smart cities and other ubiquitous monitoring applications. Their deployment, however, can be seriously hampered by the spectrum available to the sheer number of sensors for communication. To support the communication needs of UWSNs without requiring more spectrum resources, the power-domain non-orthogonal multiple access (NOMA) technique originally proposed for 5th Generation (5G) cellular networks is investigated for UWSNs for the first time in this paper. However, unlike 5G networks that operate in the licensed spectrum, UWSNs mostly operate in unlicensed spectrum where sensors also experience cross-technology interferences from other devices sharing the same spectrum. In this paper, we model the interferences from various sources at the sensors using stochastic geometry framework. To evaluate the performance, we derive a theorem and present new closed form expression for the outage probability of the sensors in a downlink scenario under interference limited environment. In addition, diversity analysis for the ordered NOMA users is performed. Based on the derived outage probability, we evaluate the average link throughput and energy consumption efficiency of NOMA against conventional orthogonal multiple access (OMA) technique in UWSNs. Further, the required computational complexity for the NOMA users is presented.

  16. Downlink Non-Orthogonal Multiple Access (NOMA) in Poisson Networks

    KAUST Repository

    Ali, Konpal S.; Haenggi, Martin; Elsawy, Hesham; Chaaban, Anas; Alouini, Mohamed-Slim

    2018-01-01

    A network model is considered where Poisson distributed base stations transmit to $N$ power-domain non-orthogonal multiple access (NOMA) users (UEs) each that employ successive interference cancellation (SIC) for decoding. We propose three models for the clustering of NOMA UEs and consider two different ordering techniques for the NOMA UEs: mean signal power-based and instantaneous signal-to-intercell-interference-and-noise-ratio-based. For each technique, we present a signal-to-interference-and-noise ratio analysis for the coverage of the typical UE. We plot the rate region for the two-user case and show that neither ordering technique is consistently superior to the other. We propose two efficient algorithms for finding a feasible resource allocation that maximize the cell sum rate $\\mathcal{R}_{\\rm tot}$, for general $N$, constrained to: 1) a minimum rate $\\mathcal{T}$ for each UE, 2) identical rates for all UEs. We show the existence of: 1) an optimum $N$ that maximizes the constrained $\\mathcal{R}_{\\rm tot}$ given a set of network parameters, 2) a critical SIC level necessary for NOMA to outperform orthogonal multiple access. The results highlight the importance in choosing the network parameters $N$, the constraints, and the ordering technique to balance the $\\mathcal{R}_{\\rm tot}$ and fairness requirements. We also show that interference-aware UE clustering can significantly improve performance.

  17. Efficient Routing in Wireless Sensor Networks with Multiple Sessions

    Directory of Open Access Journals (Sweden)

    Dianjie Lu

    2014-05-01

    Full Text Available Wireless Sensor Networks (WSNs are subject to node failures because of limited energy and link unreliability which makes the design of routing protocols in such networks a challenging task. The multipath routing scheme is an optimal alternative to address this problem which splits the traffic across multiple paths instead of routing all the traffic along a single path. However, using more paths introduces more contentions which degrade energy efficiency. The problem becomes even more difficult in the scenario of multiple sessions since different source-destination pairs may pass the same link which makes the flow distribution of each link uncertain. Our goal is to minimize the energy cost and provide the robust transmission by choosing the optimal paths. We first study the problem from a theoretical standpoint by mapping it to the multi-commodity network design problem. Since it is hard to build a global addressing scheme due to the great number of sensor nodes, we propose a Distributed Energy Efficient Routing protocol (D2ER. In D2ER, we employ the transportation method which can optimize the flow distribution with minimal energy consumption. Simulation results demonstrate that our optimal algorithm can save energy drastically.

  18. Microfluidic Devices for Studying Biomolecular Interactions

    Science.gov (United States)

    Wilson, Wilbur W.; Garcia, Carlos d.; Henry, Charles S.

    2006-01-01

    Microfluidic devices for monitoring biomolecular interactions have been invented. These devices are basically highly miniaturized liquid-chromatography columns. They are intended to be prototypes of miniature analytical devices of the laboratory on a chip type that could be fabricated rapidly and inexpensively and that, because of their small sizes, would yield analytical results from very small amounts of expensive analytes (typically, proteins). Other advantages to be gained by this scaling down of liquid-chromatography columns may include increases in resolution and speed, decreases in the consumption of reagents, and the possibility of performing multiple simultaneous and highly integrated analyses by use of multiple devices of this type, each possibly containing multiple parallel analytical microchannels. The principle of operation is the same as that of a macroscopic liquid-chromatography column: The column is a channel packed with particles, upon which are immobilized molecules of the protein of interest (or one of the proteins of interest if there are more than one). Starting at a known time, a solution or suspension containing molecules of the protein or other substance of interest is pumped into the channel at its inlet. The liquid emerging from the outlet of the channel is monitored to detect the molecules of the dissolved or suspended substance(s). The time that it takes these molecules to flow from the inlet to the outlet is a measure of the degree of interaction between the immobilized and the dissolved or suspended molecules. Depending on the precise natures of the molecules, this measure can be used for diverse purposes: examples include screening for solution conditions that favor crystallization of proteins, screening for interactions between drugs and proteins, and determining the functions of biomolecules.

  19. Optical code-division multiple-access networks

    Science.gov (United States)

    Andonovic, Ivan; Huang, Wei

    1999-04-01

    This review details the approaches adopted to implement classical code division multiple access (CDMA) principles directly in the optical domain, resulting in all optical derivatives of electronic systems. There are a number of ways of realizing all-optical CDMA systems, classified as incoherent and coherent based on spreading in the time and frequency dimensions. The review covers the basic principles of optical CDMA (OCDMA), the nature of the codes used in these approaches and the resultant limitations on system performance with respect to the number of stations (code cardinality), the number of simultaneous users (correlation characteristics of the families of codes), concluding with consideration of network implementation issues. The latest developments will be presented with respect to the integration of conventional time spread codes, used in the bulk of the demonstrations of these networks to date, with wavelength division concepts, commonplace in optical networking. Similarly, implementations based on coherent correlation with the aid of a local oscillator will be detailed and comparisons between approaches will be drawn. Conclusions regarding the viability of these approaches allowing the goal of a large, asynchronous high capacity optical network to be realized will be made.

  20. Deep convolutional neural network based antenna selection in multiple-input multiple-output system

    Science.gov (United States)

    Cai, Jiaxin; Li, Yan; Hu, Ying

    2018-03-01

    Antenna selection of wireless communication system has attracted increasing attention due to the challenge of keeping a balance between communication performance and computational complexity in large-scale Multiple-Input MultipleOutput antenna systems. Recently, deep learning based methods have achieved promising performance for large-scale data processing and analysis in many application fields. This paper is the first attempt to introduce the deep learning technique into the field of Multiple-Input Multiple-Output antenna selection in wireless communications. First, the label of attenuation coefficients channel matrix is generated by minimizing the key performance indicator of training antenna systems. Then, a deep convolutional neural network that explicitly exploits the massive latent cues of attenuation coefficients is learned on the training antenna systems. Finally, we use the adopted deep convolutional neural network to classify the channel matrix labels of test antennas and select the optimal antenna subset. Simulation experimental results demonstrate that our method can achieve better performance than the state-of-the-art baselines for data-driven based wireless antenna selection.

  1. Stability Properties of Network Diversity Multiple Access with Multiple-Antenna Reception and Imperfect Collision Multiplicity Estimation

    Directory of Open Access Journals (Sweden)

    Ramiro Samano-Robles

    2013-01-01

    Full Text Available In NDMA (network diversity multiple access, protocol-controlled retransmissions are used to create a virtual MIMO (multiple-input multiple-output system, where collisions can be resolved via source separation. By using this retransmission diversity approach for collision resolution, NDMA is the family of random access protocols with the highest potential throughput. However, several issues remain open today in the modeling and design of this type of protocol, particularly in terms of dynamic stable performance and backlog delay. This paper attempts to partially fill this gap by proposing a Markov model for the study of the dynamic-stable performance of a symmetrical and non-blind NDMA protocol assisted by a multiple-antenna receiver. The model is useful in the study of stability aspects in terms of the backlog-user distribution and average backlog delay. It also allows for the investigation of the different states of the system and the transition probabilities between them. Unlike previous works, the proposed approach considers the imperfect estimation of the collision multiplicity, which is a crucial process to the performance of NDMA. The results suggest that NDMA improves not only the throughput performance over previous solutions, but also the average number of backlogged users, the average backlog delay and, in general, the stability of random access protocols. It is also shown that when multiuser detection conditions degrade, ALOHA-type backlog retransmission becomes relevant to the stable operation of NDMA.

  2. AIR POLLUITON INDEX PREDICTION USING MULTIPLE NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Zainal Ahmad

    2017-05-01

    Full Text Available Air quality monitoring and forecasting tools are necessary for the purpose of taking precautionary measures against air pollution, such as reducing the effect of a predicted air pollution peak on the surrounding population and ecosystem. In this study a single Feed-forward Artificial Neural Network (FANN is shown to be able to predict the Air Pollution Index (API with a Mean Squared Error (MSE and coefficient determination, R2, of 0.1856 and 0.7950 respectively. However, due to the non-robust nature of single FANN, a selective combination of Multiple Neural Networks (MNN is introduced using backward elimination and a forward selection method. The results show that both selective combination methods can improve the robustness and performance of the API prediction with the MSE and R2 of 0.1614 and 0.8210 respectively. This clearly shows that it is possible to reduce the number of networks combined in MNN for API prediction, without losses of any information in terms of the performance of the final API prediction model.

  3. Multiple Transcoding Impact on Speech Quality in Ideal Network Conditions

    Directory of Open Access Journals (Sweden)

    Martin Mikulec

    2015-01-01

    Full Text Available This paper deals with the impact of transcoding on the speech quality. We have focused mainly on the transcoding between codecs without the negative influence of the network parameters such as packet loss and delay. It has ensured objective and repeatable results from our measurement. The measurement was performed on the Transcoding Measuring System developed especially for this purpose. The system is based on the open source projects and is useful as a design tool for VoIP system administrators. The paper compares the most used codecs from the transcoding perspective. The multiple transcoding between G711, GSM and G729 codecs were performed and the speech quality of these calls was evaluated. The speech quality was measured by Perceptual Evaluation of Speech Quality method, which provides results in Mean Opinion Score used to describe the speech quality on a scale from 1 to 5. The obtained results indicate periodical speech quality degradation on every transcoding between two codecs.

  4. Biomolecular simulation: historical picture and future perspectives.

    Science.gov (United States)

    van Gunsteren, Wilfred F; Dolenc, Jozica

    2008-02-01

    Over the last 30 years, computation based on molecular models is playing an increasingly important role in biology, biological chemistry and biophysics. Since only a very limited number of properties of biomolecular systems are actually accessible to measurement by experimental means, computer simulation complements experiments by providing not only averages, but also distributions and time series of any definable, observable or non-observable, quantity. Biomolecular simulation may be used (i) to interpret experimental data, (ii) to provoke new experiments, (iii) to replace experiments and (iv) to protect intellectual property. Progress over the last 30 years is sketched and perspectives are outlined for the future.

  5. Biomolecular condensates: organizers of cellular biochemistry.

    Science.gov (United States)

    Banani, Salman F; Lee, Hyun O; Hyman, Anthony A; Rosen, Michael K

    2017-05-01

    Biomolecular condensates are micron-scale compartments in eukaryotic cells that lack surrounding membranes but function to concentrate proteins and nucleic acids. These condensates are involved in diverse processes, including RNA metabolism, ribosome biogenesis, the DNA damage response and signal transduction. Recent studies have shown that liquid-liquid phase separation driven by multivalent macromolecular interactions is an important organizing principle for biomolecular condensates. With this physical framework, it is now possible to explain how the assembly, composition, physical properties and biochemical and cellular functions of these important structures are regulated.

  6. Network-based identification of biomarkers coexpressed with multiple pathways.

    Science.gov (United States)

    Guo, Nancy Lan; Wan, Ying-Wooi

    2014-01-01

    Unraveling complex molecular interactions and networks and incorporating clinical information in modeling will present a paradigm shift in molecular medicine. Embedding biological relevance via modeling molecular networks and pathways has become increasingly important for biomarker identification in cancer susceptibility and metastasis studies. Here, we give a comprehensive overview of computational methods used for biomarker identification, and provide a performance comparison of several network models used in studies of cancer susceptibility, disease progression, and prognostication. Specifically, we evaluated implication networks, Boolean networks, Bayesian networks, and Pearson's correlation networks in constructing gene coexpression networks for identifying lung cancer diagnostic and prognostic biomarkers. The results show that implication networks, implemented in Genet package, identified sets of biomarkers that generated an accurate prediction of lung cancer risk and metastases; meanwhile, implication networks revealed more biologically relevant molecular interactions than Boolean networks, Bayesian networks, and Pearson's correlation networks when evaluated with MSigDB database.

  7. Optimal assignment of multiple utilities in heat exchange networks

    International Nuclear Information System (INIS)

    Salama, A.I.A.

    2009-01-01

    Existing numerical geometry-based techniques, developed by [A.I.A. Salama, Numerical techniques for determining heat energy targets in pinch analysis, Computers and Chemical Engineering 29 (2005) 1861-1866; A.I.A. Salama, Determination of the optimal heat energy targets in heat pinch analysis using a geometry-based approach, Computers and Chemical Engineering 30 (2006) 758-764], have been extended to optimally assign multiple utilities in heat exchange network (HEN). These techniques utilize the horizontal shift between the cold composite curve (CC) and the stationary hot CC to determine the HEN optimal energy targets, grand composite curve (GCC), and the complement grand composite curve (CGCC). The proposed numerical technique developed in this paper is direct and simultaneously determines the optimal heat-energy targets and optimally assigns multiple utilities as compared with an existing technique based on sequential assignment of multiple utilities. The technique starts by arranging in an ascending order the HEN stream and target temperatures, and the resulting set is labelled T. Furthermore, the temperature sets where multiple utilities are introduced are arranged in an ascending order and are labelled T ic and T ih for the cold and hot sides, respectively. The graphical presentation of the results is facilitated by the insertion at each multiple-utility temperature a perturbed temperature equals the insertion temperature minus a small perturbation. Furthermore, using the heat exchanger network (HEN) minimum temperature-differential approach (ΔT min ) and stream heat-capacity flow rates, the presentation is facilitated by using the conventional temperature shift of the HEN CCs. The set of temperature-shifted stream and target temperatures and perturbed temperatures in the overlap range between the CCs is labelled T ol . Using T ol , a simple formula employing enthalpy-flow differences between the hot composite curve CC h and the cold composite curve CC c is

  8. Thermodynamic properties of water solvating biomolecular surfaces

    Science.gov (United States)

    Heyden, Matthias

    Changes in the potential energy and entropy of water molecules hydrating biomolecular interfaces play a significant role for biomolecular solubility and association. Free energy perturbation and thermodynamic integration methods allow calculations of free energy differences between two states from simulations. However, these methods are computationally demanding and do not provide insights into individual thermodynamic contributions, i.e. changes in the solvent energy or entropy. Here, we employ methods to spatially resolve distributions of hydration water thermodynamic properties in the vicinity of biomolecular surfaces. This allows direct insights into thermodynamic signatures of the hydration of hydrophobic and hydrophilic solvent accessible sites of proteins and small molecules and comparisons to ideal model surfaces. We correlate dynamic properties of hydration water molecules, i.e. translational and rotational mobility, to their thermodynamics. The latter can be used as a guide to extract thermodynamic information from experimental measurements of site-resolved water dynamics. Further, we study energy-entropy compensations of water at different hydration sites of biomolecular surfaces. This work is supported by the Cluster of Excellence RESOLV (EXC 1069) funded by the Deutsche Forschungsgemeinschaft.

  9. Biomolecular engineering for nanobio/bionanotechnology

    Science.gov (United States)

    Nagamune, Teruyuki

    2017-04-01

    Biomolecular engineering can be used to purposefully manipulate biomolecules, such as peptides, proteins, nucleic acids and lipids, within the framework of the relations among their structures, functions and properties, as well as their applicability to such areas as developing novel biomaterials, biosensing, bioimaging, and clinical diagnostics and therapeutics. Nanotechnology can also be used to design and tune the sizes, shapes, properties and functionality of nanomaterials. As such, there are considerable overlaps between nanotechnology and biomolecular engineering, in that both are concerned with the structure and behavior of materials on the nanometer scale or smaller. Therefore, in combination with nanotechnology, biomolecular engineering is expected to open up new fields of nanobio/bionanotechnology and to contribute to the development of novel nanobiomaterials, nanobiodevices and nanobiosystems. This review highlights recent studies using engineered biological molecules (e.g., oligonucleotides, peptides, proteins, enzymes, polysaccharides, lipids, biological cofactors and ligands) combined with functional nanomaterials in nanobio/bionanotechnology applications, including therapeutics, diagnostics, biosensing, bioanalysis and biocatalysts. Furthermore, this review focuses on five areas of recent advances in biomolecular engineering: (a) nucleic acid engineering, (b) gene engineering, (c) protein engineering, (d) chemical and enzymatic conjugation technologies, and (e) linker engineering. Precisely engineered nanobiomaterials, nanobiodevices and nanobiosystems are anticipated to emerge as next-generation platforms for bioelectronics, biosensors, biocatalysts, molecular imaging modalities, biological actuators, and biomedical applications.

  10. Converting biomolecular modelling data based on an XML representation.

    Science.gov (United States)

    Sun, Yudong; McKeever, Steve

    2008-08-25

    Biomolecular modelling has provided computational simulation based methods for investigating biological processes from quantum chemical to cellular levels. Modelling such microscopic processes requires atomic description of a biological system and conducts in fine timesteps. Consequently the simulations are extremely computationally demanding. To tackle this limitation, different biomolecular models have to be integrated in order to achieve high-performance simulations. The integration of diverse biomolecular models needs to convert molecular data between different data representations of different models. This data conversion is often non-trivial, requires extensive human input and is inevitably error prone. In this paper we present an automated data conversion method for biomolecular simulations between molecular dynamics and quantum mechanics/molecular mechanics models. Our approach is developed around an XML data representation called BioSimML (Biomolecular Simulation Markup Language). BioSimML provides a domain specific data representation for biomolecular modelling which can effciently support data interoperability between different biomolecular simulation models and data formats.

  11. Optimization of Multiple Related Negotiation through Multi-Negotiation Network

    Science.gov (United States)

    Ren, Fenghui; Zhang, Minjie; Miao, Chunyan; Shen, Zhiqi

    In this paper, a Multi-Negotiation Network (MNN) and a Multi- Negotiation Influence Diagram (MNID) are proposed to optimally handle Multiple Related Negotiations (MRN) in a multi-agent system. Most popular, state-of-the-art approaches perform MRN sequentially. However, a sequential procedure may not optimally execute MRN in terms of maximizing the global outcome, and may even lead to unnecessary losses in some situations. The motivation of this research is to use a MNN to handle MRN concurrently so as to maximize the expected utility of MRN. Firstly, both the joint success rate and the joint utility by considering all related negotiations are dynamically calculated based on a MNN. Secondly, by employing a MNID, an agent's possible decision on each related negotiation is reflected by the value of expected utility. Lastly, through comparing expected utilities between all possible policies to conduct MRN, an optimal policy is generated to optimize the global outcome of MRN. The experimental results indicate that the proposed approach can improve the global outcome of MRN in a successful end scenario, and avoid unnecessary losses in an unsuccessful end scenario.

  12. Multiple Hub Network Choice in the Liberalized European Market

    Science.gov (United States)

    Berechman, Joseph; deWit, Jaap

    1997-01-01

    . In the meantime, open skies agreements have been concluded between the USA and most of the EU member states to facilitate strategic alliances between airlines of the states involved. As a result of this on-going liberalization the model of the single 'national' carrier using the national home base as its single hub for the designated third, fourth and sixth freedom operations will stepwise disappear. Within the EU the concept of the national carrier has already been replaced by that of the community carrier. State ownership in more and more European carriers is reduced. On the longer run mergers or even bankruptcy will further undermine the "single national carrier - single national hub" model in Europe. In the meantime, strategic alliances between national carriers in Europe will already reduce the airlines' loyalty to a single airport. Profit maximization and accountability to share holders will supersede the loyalty of these newly emerging alliances, probably looking for the opportunities of a multiple hub network to adequately cover the whole European market. As a consequence, some European airports might see a substantial decline in arriving, departing and transfer traffic, thus in revenues and financial solvency, as well as in their connection to other inter-continental and intra-European destinations. At the same time, other airports might realize a significant increase in traffic as they will be sought after by the profit maximizing airlines as their major gateway hubs. Which will be the losing airports and which will be the winning ones? Can airports anticipate the actions of airlines in deregulated markets and utilize policies which will improve their relative position? If so, what should be these anticipatory policies? These questions become the more urgent, since an increasing number of major European airports will be privatized in the near future. Although increasing airport congestion in Europe will also be reflected in a growing demand pressure for

  13. Multiple dynamical time-scales in networks with hierarchically ...

    Indian Academy of Sciences (India)

    cists from resistor networks to polymer contact structure to spin interactions in disordered ... the intracellular signalling system to neuronal networks to ecological food ... tion of the key players can be used to develop drugs targeted specifically ...

  14. Performance Analysis on the Coexistence of Multiple Cognitive Radio Networks

    Science.gov (United States)

    2015-05-28

    etc. The regulation of wireless networks is done by government agencies through which spectrum is allocated to a particular application , this kind of...Local Area Networks ( WLAN ), cordless phones and BluetoothWireless Personal Area Networks (WPAN). While unlicensed bands have opened up avenues for the...they can be applied to other types of wireless ad hoc networks. As an example, this framework finds application in Device-to-Device (D2D) communication

  15. Network formation under heterogeneous costs: The multiple group model

    NARCIS (Netherlands)

    Kamphorst, J.J.A.; van der Laan, G.

    2007-01-01

    It is widely recognized that the shape of networks influences both individual and aggregate behavior. This raises the question which types of networks are likely to arise. In this paper we investigate a model of network formation, where players are divided into groups and the costs of a link between

  16. Anti-synchronization control of BAM memristive neural networks with multiple proportional delays and stochastic perturbations

    Science.gov (United States)

    Wang, Weiping; Yuan, Manman; Luo, Xiong; Liu, Linlin; Zhang, Yao

    2018-01-01

    Proportional delay is a class of unbounded time-varying delay. A class of bidirectional associative memory (BAM) memristive neural networks with multiple proportional delays is concerned in this paper. First, we propose the model of BAM memristive neural networks with multiple proportional delays and stochastic perturbations. Furthermore, by choosing suitable nonlinear variable transformations, the BAM memristive neural networks with multiple proportional delays can be transformed into the BAM memristive neural networks with constant delays. Based on the drive-response system concept, differential inclusions theory and Lyapunov stability theory, some anti-synchronization criteria are obtained. Finally, the effectiveness of proposed criteria are demonstrated through numerical examples.

  17. Remoting alternatives for a multiple phased-array antenna network

    Science.gov (United States)

    Shi, Zan; Foshee, James J.

    2001-10-01

    Significant improvements in technology have made phased array antennas an attractive alternative to the traditional dish antenna for use on wide body airplanes. These improvements have resulted in reduced size, reduced cost, reduced losses in the transmit and receive channels (simplifying the design), a significant extension in the bandwidth capability, and an increase in the functional capability. Flush mounting (thus reduced drag) and rapid beam switching are among the evolving desirable features of phased array antennas. Beam scanning of phased array antennas is limited to +/-45 degrees at best and therefore multiple phased array antennas would need to be used to insure instantaneous communications with any ground station (stations located at different geographical locations on the ground) and with other airborne stations. The exact number of phased array antennas and the specific installation location of each antenna on the wide body airplane would need to be determined by the specific communication requirements, but it is conceivable as many as five phased array antennas may need to be used to provide the required coverage. Control and switching of these antennas would need to be accomplished at a centralized location on the airplane and since these antennas would be at different locations on the airplane an efficient scheme of remoting would need to be used. To save in cost and keep the phased array antennas as small as possible the design of the phased array antennas would need to be kept simple. A dish antenna and a blade antenna (small size) could also be used to augment the system. Generating the RF signals at the central location and then using RF cables or waveguide to get the signal to any given antenna could result in significant RF losses. This paper will evaluate a number of remoting alternatives to keep the system design simple, reduce system cost, and utilize the functional capability of networking multiple phased array antennas on a wide body

  18. Application of neural networks to multiple alarm processing and diagnosis in nuclear power plants

    International Nuclear Information System (INIS)

    Cheon, Se Woo; Chang Soon Heung; Chung, Hak Yeong

    1992-01-01

    This paper presents feasibility studies of multiple alarm processing and diagnosis using neural networks. The back-propagation neural network model is applied to the training of multiple alarm patterns for the identification of failure in a reactor coolant pump (RCP) system. The general mapping capability of the neural network enables to identify a fault easily. The case studies are performed with emphasis on the applicability of the neural network to pattern recognition problems. It is revealed that the neural network model can identify the cause of multiple alarms properly, even when untrained or sensor-failed alarm symptoms are given. It is also shown that multiple failures are easily identified using the symptoms of multiple alarms

  19. Ordering, materiality, and multiplicity: Enacting Actor–Network Theory in tourism

    NARCIS (Netherlands)

    Duim, van der R.; Ren, C.; Johannesson, G.T.

    2013-01-01

    In this article, we demonstrate how Actor–Network Theory has been translated into tourism research. The article presents and discusses three concepts integral to the Actor–Network Theory approach: ordering, materiality, and multiplicity. We first briefly introduce Actor–Network Theory and draw

  20. Lower Bounds on the Maximum Energy Benefit of Network Coding for Wireless Multiple Unicast

    NARCIS (Netherlands)

    Goseling, J.; Matsumoto, R.; Uyematsu, T.; Weber, J.H.

    2010-01-01

    We consider the energy savings that can be obtained by employing network coding instead of plain routing in wireless multiple unicast problems. We establish lower bounds on the benefit of network coding, defined as the maximum of the ratio of the minimum energy required by routing and network coding

  1. Lower bounds on the maximum energy benefit of network coding for wireless multiple unicast

    NARCIS (Netherlands)

    Goseling, Jasper; Matsumoto, Ryutaroh; Uyematsu, Tomohiko; Weber, Jos H.

    2010-01-01

    We consider the energy savings that can be obtained by employing network coding instead of plain routing in wireless multiple unicast problems. We establish lower bounds on the benefit of network coding, defined as the maximum of the ratio of the minimum energy required by routing and network coding

  2. Robustness analysis of interdependent networks under multiple-attacking strategies

    Science.gov (United States)

    Gao, Yan-Li; Chen, Shi-Ming; Nie, Sen; Ma, Fei; Guan, Jun-Jie

    2018-04-01

    The robustness of complex networks under attacks largely depends on the structure of a network and the nature of the attacks. Previous research on interdependent networks has focused on two types of initial attack: random attack and degree-based targeted attack. In this paper, a deliberate attack function is proposed, where six kinds of deliberate attacking strategies can be derived by adjusting the tunable parameters. Moreover, the robustness of four types of interdependent networks (BA-BA, ER-ER, BA-ER and ER-BA) with different coupling modes (random, positive and negative correlation) is evaluated under different attacking strategies. Interesting conclusions could be obtained. It can be found that the positive coupling mode can make the vulnerability of the interdependent network to be absolutely dependent on the most vulnerable sub-network under deliberate attacks, whereas random and negative coupling modes make the vulnerability of interdependent network to be mainly dependent on the being attacked sub-network. The robustness of interdependent network will be enhanced with the degree-degree correlation coefficient varying from positive to negative. Therefore, The negative coupling mode is relatively more optimal than others, which can substantially improve the robustness of the ER-ER network and ER-BA network. In terms of the attacking strategies on interdependent networks, the degree information of node is more valuable than the betweenness. In addition, we found a more efficient attacking strategy for each coupled interdependent network and proposed the corresponding protection strategy for suppressing cascading failure. Our results can be very useful for safety design and protection of interdependent networks.

  3. Application of Nanodiamonds in Biomolecular Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Ping Cheng

    2010-03-01

    Full Text Available The combination of nanodiamond (ND with biomolecular mass spectrometry (MS makes rapid, sensitive detection of biopolymers from complex biosamples feasible. Due to its chemical inertness, optical transparency and biocompatibility, the advantage of NDs in MS study is unique. Furthermore, functionalization on the surfaces of NDs expands their application in the fields of proteomics and genomics for specific requirements greatly. This review presents methods of MS analysis based on solid phase extraction and elution on NDs and different application examples including peptide, protein, DNA, glycan and others. Owing to the quick development of nanotechnology, surface chemistry, new MS methods and the intense interest in proteomics and genomics, a huge increase of their applications in biomolecular MS analysis in the near future can be predicted.

  4. PREFACE: Radiation Damage in Biomolecular Systems (RADAM07)

    Science.gov (United States)

    McGuigan, Kevin G.

    2008-03-01

    , which include: theoretical, experimental, medical and computational physicists, radiation chemists, radiation biologists and microbiologists, among others. An important aspect of the previous 3 conferences in this series was to remove barriers between the different working groups and to encourage a more interdisciplinary approach to research collaborations. During RADAM_07 we could observe the success of these efforts. A large number of presentations were based on new collaborations, many funded under the COST STSM programme, and all presentations led to lively discussions. It is clear from the discussions following many of the presentations and at the poster sessions that Radiation Damage in Biomolecular Systems remains a topic of increasing interest, relevance and importance. The success of this conference as well as of the whole RADAM conference series reflects the growing international interest in the area of interactions of ionizing radiation with biomolecules. Despite the scheduled conclusion in September 2007 of COST Action P9 which has part-funded this, and previous RADAM meetings, the nature of the cross-disciplinary interactions and opportunities for collaborative research was deemed so successful and valuable by the assembled delegates that it was agreed that another such meeting should be held in Debrecen in Hungary from 13-15 June 2008 http://www.isa.au.dk/meetings/radam2008/programme.html. Additional information about RADAM07 programme is available on the conference web-page http://www.isa.au.dk/networks/cost/radam07/index.html. The Organizing Committee would like to thank all speakers, contributors, session chairs, referees and meeting staff for their efforts in making the RADAM07 successful. The local Organization Committee would like to thank Lorraine Monard and Margaret Nolan for their invaluable expertise in conference management. We also gratefully acknowledge the financial support of our sponsors - The Royal, College of Surgeons in Ireland (RCSI

  5. Biomolecular electrostatics and solvation: a computational perspective.

    Science.gov (United States)

    Ren, Pengyu; Chun, Jaehun; Thomas, Dennis G; Schnieders, Michael J; Marucho, Marcelo; Zhang, Jiajing; Baker, Nathan A

    2012-11-01

    An understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis, and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. This review discusses the solvation of biomolecules with a computational biophysics view toward describing the phenomenon. While our main focus lies on the computational aspect of the models, we provide an overview of the basic elements of biomolecular solvation (e.g. solvent structure, polarization, ion binding, and non-polar behavior) in order to provide a background to understand the different types of solvation models.

  6. NMRbox: A Resource for Biomolecular NMR Computation.

    Science.gov (United States)

    Maciejewski, Mark W; Schuyler, Adam D; Gryk, Michael R; Moraru, Ion I; Romero, Pedro R; Ulrich, Eldon L; Eghbalnia, Hamid R; Livny, Miron; Delaglio, Frank; Hoch, Jeffrey C

    2017-04-25

    Advances in computation have been enabling many recent advances in biomolecular applications of NMR. Due to the wide diversity of applications of NMR, the number and variety of software packages for processing and analyzing NMR data is quite large, with labs relying on dozens, if not hundreds of software packages. Discovery, acquisition, installation, and maintenance of all these packages is a burdensome task. Because the majority of software packages originate in academic labs, persistence of the software is compromised when developers graduate, funding ceases, or investigators turn to other projects. To simplify access to and use of biomolecular NMR software, foster persistence, and enhance reproducibility of computational workflows, we have developed NMRbox, a shared resource for NMR software and computation. NMRbox employs virtualization to provide a comprehensive software environment preconfigured with hundreds of software packages, available as a downloadable virtual machine or as a Platform-as-a-Service supported by a dedicated compute cloud. Ongoing development includes a metadata harvester to regularize, annotate, and preserve workflows and facilitate and enhance data depositions to BioMagResBank, and tools for Bayesian inference to enhance the robustness and extensibility of computational analyses. In addition to facilitating use and preservation of the rich and dynamic software environment for biomolecular NMR, NMRbox fosters the development and deployment of a new class of metasoftware packages. NMRbox is freely available to not-for-profit users. Copyright © 2017 Biophysical Society. All rights reserved.

  7. Design of an embedded inverse-feedforward biomolecular tracking controller for enzymatic reaction processes.

    Science.gov (United States)

    Foo, Mathias; Kim, Jongrae; Sawlekar, Rucha; Bates, Declan G

    2017-04-06

    Feedback control is widely used in chemical engineering to improve the performance and robustness of chemical processes. Feedback controllers require a 'subtractor' that is able to compute the error between the process output and the reference signal. In the case of embedded biomolecular control circuits, subtractors designed using standard chemical reaction network theory can only realise one-sided subtraction, rendering standard controller design approaches inadequate. Here, we show how a biomolecular controller that allows tracking of required changes in the outputs of enzymatic reaction processes can be designed and implemented within the framework of chemical reaction network theory. The controller architecture employs an inversion-based feedforward controller that compensates for the limitations of the one-sided subtractor that generates the error signals for a feedback controller. The proposed approach requires significantly fewer chemical reactions to implement than alternative designs, and should have wide applicability throughout the fields of synthetic biology and biological engineering.

  8. An optics-based variable-temperature assay system for characterizing thermodynamics of biomolecular reactions on solid support

    Energy Technology Data Exchange (ETDEWEB)

    Fei, Yiyan; Landry, James P.; Zhu, X. D., E-mail: xdzhu@physics.ucdavis.edu [Department of Physics, University of California, One Shields Avenue, Davis, California 95616 (United States); Li, Yanhong; Yu, Hai; Lau, Kam; Huang, Shengshu; Chokhawala, Harshal A.; Chen, Xi [Department of Chemistry, University of California, One Shields Avenue, Davis, California 95616 (United States)

    2013-11-15

    A biological state is equilibrium of multiple concurrent biomolecular reactions. The relative importance of these reactions depends on physiological temperature typically between 10 °C and 50 °C. Experimentally the temperature dependence of binding reaction constants reveals thermodynamics and thus details of these biomolecular processes. We developed a variable-temperature opto-fluidic system for real-time measurement of multiple (400–10 000) biomolecular binding reactions on solid supports from 10 °C to 60 °C within ±0.1 °C. We illustrate the performance of this system with investigation of binding reactions of plant lectins (carbohydrate-binding proteins) with 24 synthetic glycans (i.e., carbohydrates). We found that the lectin-glycan reactions in general can be enthalpy-driven, entropy-driven, or both, and water molecules play critical roles in the thermodynamics of these reactions.

  9. A statistical nanomechanism of biomolecular patterning actuated by surface potential

    Science.gov (United States)

    Lin, Chih-Ting; Lin, Chih-Hao

    2011-02-01

    Biomolecular patterning on a nanoscale/microscale on chip surfaces is one of the most important techniques used in vitro biochip technologies. Here, we report upon a stochastic mechanics model we have developed for biomolecular patterning controlled by surface potential. The probabilistic biomolecular surface adsorption behavior can be modeled by considering the potential difference between the binding and nonbinding states. To verify our model, we experimentally implemented a method of electroactivated biomolecular patterning technology and the resulting fluorescence intensity matched the prediction of the developed model quite well. Based on this result, we also experimentally demonstrated the creation of a bovine serum albumin pattern with a width of 200 nm in 5 min operations. This submicron noncovalent-binding biomolecular pattern can be maintained for hours after removing the applied electrical voltage. These stochastic understandings and experimental results not only prove the feasibility of submicron biomolecular patterns on chips but also pave the way for nanoscale interfacial-bioelectrical engineering.

  10. The US Network of Pediatric Multiple Sclerosis Centers: Development, Progress, and Next Steps

    Science.gov (United States)

    Casper, T. Charles; Rose, John W.; Roalstad, Shelly; Waubant, Emmanuelle; Aaen, Gregory; Belman, Anita; Chitnis, Tanuja; Gorman, Mark; Krupp, Lauren; Lotze, Timothy E.; Ness, Jayne; Patterson, Marc; Rodriguez, Moses; Weinstock-Guttman, Bianca; Browning, Brittan; Graves, Jennifer; Tillema, Jan-Mendelt; Benson, Leslie; Harris, Yolanda

    2014-01-01

    Multiple sclerosis and other demyelinating diseases in the pediatric population have received an increasing level of attention by clinicians and researchers. The low incidence of these diseases in children creates a need for the involvement of multiple clinical centers in research efforts. The Network of Pediatric Multiple Sclerosis Centers was created initially in 2006 to improve the diagnosis and care of children with demyelinating diseases. In 2010, the Network shifted its focus to multicenter research while continuing to advance the care of patients. The Network has obtained support from the National Multiple Sclerosis Society, the Guthy-Jackson Charitable Foundation, and the National Institutes of Health. The Network will continue to serve as a platform for conducting impactful research in pediatric demyelinating diseases of the central nervous system. This article provides a description of the history and development, organization, mission, research priorities, current studies, and future plans of the Network. PMID:25270659

  11. Design of an embedded inverse-feedforward biomolecular tracking controller for enzymatic reaction processes

    OpenAIRE

    Foo, Mathias; Kim, Jongrae; Sawlekar, Rucha; Bates, Declan G.

    2017-01-01

    Feedback control is widely used in chemical engineering to improve the performance and robustness of chemical processes. Feedback controllers require a ‘subtractor’ that is able to compute the error between the process output and the reference signal. In the case of embedded biomolecular control circuits, subtractors designed using standard chemical reaction network theory can only realise one-sided subtraction, rendering standard controller design approaches inadequate. Here, we show how a b...

  12. Multiple dynamical time-scales in networks with hierarchically

    Indian Academy of Sciences (India)

    Modular networks; hierarchical organization; synchronization. ... we show that such a topological structure gives rise to characteristic time-scale separation ... This suggests a possible functional role of such mesoscopic organization principle in ...

  13. 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

  14. 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.

  15. CyLineUp: A Cytoscape app for visualizing data in network small multiples.

    Science.gov (United States)

    Costa, Maria Cecília D; Slijkhuis, Thijs; Ligterink, Wilco; Hilhorst, Henk W M; de Ridder, Dick; Nijveen, Harm

    2016-01-01

    CyLineUp is a Cytoscape 3 app for the projection of high-throughput measurement data from multiple experiments/samples on a network or pathway map using "small multiples". This visualization method allows for easy comparison of different experiments in the context of the network or pathway. The user can import various kinds of measurement data and select any appropriate Cytoscape network or WikiPathways pathway map. CyLineUp creates small multiples by replicating the loaded network as many times as there are experiments/samples (e.g. time points, stress conditions, tissues, etc.). The measurement data for each experiment are then mapped onto the nodes (genes, proteins etc.) of the corresponding network using a color gradient. Each step of creating the visualization can be customized to the user's needs. The results can be exported as a high quality vector image.

  16. Multi-Destination Cognitive Radio Relay Network with SWIPT and Multiple Primary Receivers

    KAUST Repository

    Al-Habob, Ahmed A.; Salhab, Anas M.; Zummo, Salam A.; Alouini, Mohamed-Slim

    2017-01-01

    In this paper, we study the performance of simultaneous wireless information and power transfer (SWIPT) technique in a multi-destination dual-hop underlay cognitive relay network with multiple primary receivers. Information transmission from

  17. Energy efficient design for MIMO two-way AF multiple relay networks

    KAUST Repository

    Alsharoa, Ahmad M.; Ghazzai, Hakim; Alouini, Mohamed-Slim

    2014-01-01

    This paper studies the energy efficient transmission and the power allocation problem for multiple two-way relay networks equipped with multi-input multi-output antennas where each relay employs an amplify-and-forward strategy. The goal

  18. Optimal power allocation of a single transmitter-multiple receivers channel in a cognitive sensor network

    KAUST Repository

    Ayala Solares, Jose Roberto; Rezki, Zouheir; Alouini, Mohamed-Slim

    2012-01-01

    The optimal transmit power of a wireless sensor network with one transmitter and multiple receivers in a cognitive radio environment while satisfying independent peak, independent average, sum of peak and sum of average transmission rate constraints

  19. A genetic algorithm for multiple relay selection in two-way relaying cognitive radio networks

    KAUST Repository

    Alsharoa, Ahmad M.; Ghazzai, Hakim; Alouini, Mohamed-Slim

    2013-01-01

    In this paper, we investigate a multiple relay selection scheme for two-way relaying cognitive radio networks where primary users and secondary users operate on the same frequency band. More specifically, cooperative relays using Amplifyand- Forward

  20. Safe design and operation of tank reactors for multiple-reaction networks: uniqueness and multiplicity

    NARCIS (Netherlands)

    Westerterp, K.R.; Westerink, E.J.

    1990-01-01

    A method is developed to design a tank reactor in which a network of reactions is carried out. The network is a combination of parallel and consecutive reactions. The method ensures unique operation. Dimensionless groups are used which are either representative of properties of the reaction system

  1. Scalable Molecular Dynamics for Large Biomolecular Systems

    Directory of Open Access Journals (Sweden)

    Robert K. Brunner

    2000-01-01

    Full Text Available We present an optimized parallelization scheme for molecular dynamics simulations of large biomolecular systems, implemented in the production-quality molecular dynamics program NAMD. With an object-based hybrid force and spatial decomposition scheme, and an aggressive measurement-based predictive load balancing framework, we have attained speeds and speedups that are much higher than any reported in literature so far. The paper first summarizes the broad methodology we are pursuing, and the basic parallelization scheme we used. It then describes the optimizations that were instrumental in increasing performance, and presents performance results on benchmark simulations.

  2. Micro and Nanotechnologies Enhanced Biomolecular Sensing

    Directory of Open Access Journals (Sweden)

    Tza-Huei Wang

    2013-07-01

    Full Text Available This editorial summarizes some of the recent advances of micro and nanotechnology-based tools and devices for biomolecular detection. These include the incorporation of nanomaterials into a sensor surface or directly interfacing with molecular probes to enhance target detection via more rapid and sensitive responses, and the use of self-assembled organic/inorganic nanocomposites that inhibit exceptional spectroscopic properties to enable facile homogenous assays with efficient binding kinetics. Discussions also include some insight into microfluidic principles behind the development of an integrated sample preparation and biosensor platform toward a miniaturized and fully functional system for point of care applications.

  3. Embedding multiple self-organisation functionalities in future radio access networks

    NARCIS (Netherlands)

    Jansen, T.; Amirijoo, M.; Türke, U.; Jorguseski, L.; Zetterberg, K.; Nascimento, J.R.V. do; Schmelz, L.C.; Turk, J.; Balan, I.

    2009-01-01

    Wireless network operators today allocate considerable manual effort in managing their networks. A viable solution for lowering the manual effort is to introduce self-organisation functionalities. In this paper we discuss the challenges that are encountered when embedding multiple self-organisation

  4. Implementing multiple intervention strategies in Dutch public health-related policy networks

    NARCIS (Netherlands)

    Harting, Janneke; Peters, Dorothee; Grêaux, Kimberly; van Assema, Patricia; Verweij, Stefan; Stronks, Karien; Klijn, Erik-Hans

    2017-01-01

    Improving public health requires multiple intervention strategies. Implementing such an intervention mix is supposed to require a multisectoral policy network. As evidence to support this assumption is scarce, we examined under which conditions public health-related policy networks were able to

  5. Heirloom biodynamic seeds network rescue, conservation and multiplication of local seeds in Brazil

    OpenAIRE

    Jovchelevich, Pedro

    2014-01-01

    Structuring a network organic and biodynamic seed involving farmers in the central- southern Brazil. Training, participatory breeding, edition of publications, fairs of exchange seeds, a processing unit and assessment of seed quality, commercial seed multiplication with emphasis on vegetables. This network has garanteed the autonomy of farmers in seed production and enriched agrobiodiversity through exchanges of seed.

  6. Actor-Network Theory and Tourism : Ordering, materiality and multiplicity

    NARCIS (Netherlands)

    Duim, van der V.R.; Ren, C.; Jóhannesson, G.T.

    2012-01-01

    The recent surfacing of actor-network theory (ANT) in tourism studies correlates to a rising interest in understanding tourism as emergent thorough relational practice connecting cultures, natures and technologies in multifarious ways. Despite the widespread application of ANT across the social

  7. Multiple Description Coding with Feedback Based Network Compression

    DEFF Research Database (Denmark)

    Sørensen, Jesper Hemming; Østergaard, Jan; Popovski, Petar

    2010-01-01

    and an intermediate node, respectively. A trade-off exists between reducing the delay of the feedback by adapting in the vicinity of the receiver and increasing the gain from compression by adapting close to the source. The analysis shows that adaptation in the network provides a better trade-off than adaptation...

  8. Adaptive Information Access on Multiple Applications Support Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Tobgay, Sonam; Olsen, Rasmus Løvenstein; Prasad, Ramjee

    2014-01-01

    information is challenged by dynamic nature of information elements. These challenges are more prominent in case of wireless sensor network (WSN) applications, as the information that the sensor node collects are mostly dynamic in nature (say, temperature). Therefore, it is likely that there can be a mismatch...

  9. Adaptive Information Access in Multiple Applications Support Wireless Sensor Network

    DEFF Research Database (Denmark)

    Tobgay, Sonam; Olsen, Rasmus Løvenstein; Prasad, Ramjee

    2012-01-01

    Nowadays, due to wide applicability of Wireless Sensor Network (WSN) added by the low cost sensor devices, its popularity among the researchers and industrialists are very much visible. A substantial amount of works can be seen in the literature on WSN which are mainly focused on application...

  10. Injectivity, multiple zeros, and multistationarity in reaction networks

    DEFF Research Database (Denmark)

    Feliu, Elisenda

    2015-01-01

    Polynomial dynamical systems are widely used to model and study real phenomena. In biochemistry, they are the preferred choice for modelling the concentration of chemical species in reaction networks with mass-action kinetics. These systems are typically parametrized by many (unknown) parameters...

  11. Default mode network links to visual hallucinations: A comparison between Parkinson's disease and multiple system atrophy.

    Science.gov (United States)

    Franciotti, Raffaella; Delli Pizzi, Stefano; Perfetti, Bernardo; Tartaro, Armando; Bonanni, Laura; Thomas, Astrid; Weis, Luca; Biundo, Roberta; Antonini, Angelo; Onofrj, Marco

    2015-08-01

    Studying default mode network activity or connectivity in different parkinsonisms, with or without visual hallucinations, could highlight its roles in clinical phenotypes' expression. Multiple system atrophy is the archetype of parkinsonism without visual hallucinations, variably appearing instead in Parkinson's disease (PD). We aimed to evaluate default mode network functions in multiple system atrophy in comparison with PD. Functional magnetic resonance imaging evaluated default mode network activity and connectivity in 15 multiple system atrophy patients, 15 healthy controls, 15 early PD patients matched for disease duration, 30 severe PD patients (15 with and 15 without visual hallucinations), matched with multiple system atrophy for disease severity. Cortical thickness and neuropsychological evaluations were also performed. Multiple system atrophy had reduced default mode network activity compared with controls and PD with hallucinations, and no differences with PD (early or severe) without hallucinations. In PD with visual hallucinations, activity and connectivity was preserved compared with controls and higher than in other groups. In early PD, connectivity was lower than in controls but higher than in multiple system atrophy and severe PD without hallucinations. Cortical thickness was reduced in severe PD, with and without hallucinations, and correlated only with disease duration. Higher anxiety scores were found in patients without hallucinations. Default mode network activity and connectivity was higher in PD with visual hallucinations and reduced in multiple system atrophy and PD without visual hallucinations. Cortical thickness comparisons suggest that functional, rather than structural, changes underlie the activity and connectivity differences. © 2015 International Parkinson and Movement Disorder Society.

  12. Networks in Argentine agriculture: a multiple-case study approach

    Directory of Open Access Journals (Sweden)

    Sebastián Senesi

    2013-06-01

    Full Text Available Argentina is among the four largest producers of soybeans, sunflower, corn, and wheat, among other agricultural products. Institutional and policy changes during the 1990s fostered the development of Argentine agriculture and the introduction of innovative process and product technologies (no-till, agrochemicals, GMO, GPS and new investments in modern, large-scale sunflower and soybean processing plants. In addition to technological changes, a "quiet revolution" occurred in the way agricultural production was carried out and organized: from self-production or ownership agriculture to a contract-based agriculture. The objective of this paper is to explore and describe the emergence of networks in the Argentine crop production sector. The paper presents and describes four cases that currently represent about 50% of total grain and oilseed production in Argentina: "informal hybrid form", "agricultural trust fund", "investor-oriented corporate structure", and "network of networks". In all cases, hybrid forms involve a group of actors linked by common objectives, mainly to gain scale, share resources, and improve the profitability of the business. Informal contracts seem to be the most common way of organizing the agriculture process, but using short-term contracts and sequential interfirm collaboration. Networks of networks involve long-term relationships and social development, and reciprocal interfirm collaboration. Agricultural trust fund and investor-oriented corporate structures have combined interfirm collaboration and medium-term relationships. These organizational forms are highly flexible and show a great capacity to adapt to challenges; they are competitive because they enjoy aligned incentives, flexibility, and adaptability.

  13. Relative camera localisation in non-overlapping camera networks using multiple trajectories

    NARCIS (Netherlands)

    John, V.; Englebienne, G.; Kröse, B.J.A.

    2012-01-01

    In this article we present an automatic camera calibration algorithm using multiple trajectories in a multiple camera network with non-overlapping field-of-views (FOV). Visible trajectories within a camera FOV are assumed to be measured with respect to the camera local co-ordinate system.

  14. Serial network simplifies the design of multiple microcomputer systems

    Energy Technology Data Exchange (ETDEWEB)

    Folkes, D.

    1981-01-01

    Recently there has been a lot of interest in developing network communication schemes for carrying digital data between locally distributed computing stations. Many of these schemes have focused on distributed networking techniques for data processing applications. These applications suggest the use of a serial, multipoint bus, where a number of remote intelligent units act as slaves to a central or host computer. Each slave would be serially addressable from the host and would perform required operations upon being addressed by the host. Based on an MK3873 single-chip microcomputer, the SCU 20 is designed to be such a remote slave device. The capabilities of the SCU 20 and its use in systems applications are examined.

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

    Science.gov (United States)

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

    2018-04-16

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

  16. Pareto evolution of gene networks: an algorithm to optimize multiple fitness objectives

    International Nuclear Information System (INIS)

    Warmflash, Aryeh; Siggia, Eric D; Francois, Paul

    2012-01-01

    The computational evolution of gene networks functions like a forward genetic screen to generate, without preconceptions, all networks that can be assembled from a defined list of parts to implement a given function. Frequently networks are subject to multiple design criteria that cannot all be optimized simultaneously. To explore how these tradeoffs interact with evolution, we implement Pareto optimization in the context of gene network evolution. In response to a temporal pulse of a signal, we evolve networks whose output turns on slowly after the pulse begins, and shuts down rapidly when the pulse terminates. The best performing networks under our conditions do not fall into categories such as feed forward and negative feedback that also encode the input–output relation we used for selection. Pareto evolution can more efficiently search the space of networks than optimization based on a single ad hoc combination of the design criteria. (paper)

  17. Pareto evolution of gene networks: an algorithm to optimize multiple fitness objectives.

    Science.gov (United States)

    Warmflash, Aryeh; Francois, Paul; Siggia, Eric D

    2012-10-01

    The computational evolution of gene networks functions like a forward genetic screen to generate, without preconceptions, all networks that can be assembled from a defined list of parts to implement a given function. Frequently networks are subject to multiple design criteria that cannot all be optimized simultaneously. To explore how these tradeoffs interact with evolution, we implement Pareto optimization in the context of gene network evolution. In response to a temporal pulse of a signal, we evolve networks whose output turns on slowly after the pulse begins, and shuts down rapidly when the pulse terminates. The best performing networks under our conditions do not fall into categories such as feed forward and negative feedback that also encode the input-output relation we used for selection. Pareto evolution can more efficiently search the space of networks than optimization based on a single ad hoc combination of the design criteria.

  18. Multiple Resting-State Networks Are Associated With Tremors and Cognitive Features in Essential Tremor.

    Science.gov (United States)

    Fang, Weidong; Chen, Huiyue; Wang, Hansheng; Zhang, Han; Liu, Mengqi; Puneet, Munankami; Lv, Fajin; Cheng, Oumei; Wang, Xuefeng; Lu, Xiurong; Luo, Tianyou

    2015-12-01

    The heterogeneous clinical features of essential tremor indicate that the dysfunctions of this syndrome are not confined to motor networks, but extend to nonmotor networks. Currently, these neural network dysfunctions in essential tremor remain unclear. In this study, independent component analysis of resting-state functional MRI was used to study these neural network mechanisms. Thirty-five essential tremor patients and 35 matched healthy controls with clinical and neuropsychological tests were included, and eight resting-state networks were identified. After considering the structure and head-motion factors and testing the reliability of the selected resting-state networks, we assessed the functional connectivity changes within or between resting-state networks. Finally, image-behavior correlation analysis was performed. Compared to healthy controls, essential tremor patients displayed increased functional connectivity in the sensorimotor and salience networks and decreased functional connectivity in the cerebellum network. Additionally, increased functional network connectivity was observed between anterior and posterior default mode networks, and a decreased functional network connectivity was noted between the cerebellum network and the sensorimotor and posterior default mode networks. Importantly, the functional connectivity changes within and between these resting-state networks were correlated with the tremor severity and total cognitive scores of essential tremor patients. The findings of this study provide the first evidence that functional connectivity changes within and between multiple resting-state networks are associated with tremors and cognitive features of essential tremor, and this work demonstrates a potential approach for identifying the underlying neural network mechanisms of this syndrome. © 2015 International Parkinson and Movement Disorder Society.

  19. Position paper: cognitive radio networking for multiple sensor network interoperability in mines

    CSIR Research Space (South Africa)

    Kagize, BM

    2008-01-01

    Full Text Available . These commercially available networks are purported to be self-organizing and self correcting, though the software behind these networks are proprietary with the caveat of inter-operability difficulties with other networks [5]. There is a non-propriety and open...: Research challenges,” - Ad Hoc Networks, 2006 – Elsevier [4] V Mhatre, C Rosenberg, “Homogeneous vs heterogeneous clustered sensor networks: a comparative study,” - Communications, 2004 IEEE International Conference on, 2004 - ieeexplore.ieee.org [5...

  20. Converting Biomolecular Modelling Data Based on an XML Representation

    Directory of Open Access Journals (Sweden)

    Sun Yudong

    2008-06-01

    Full Text Available Biomolecular modelling has provided computational simulation based methods for investigating biological processes from quantum chemical to cellular levels. Modelling such microscopic processes requires atomic description of a biological system and conducts in fine timesteps. Consequently the simulations are extremely computationally demanding. To tackle this limitation, different biomolecular models have to be integrated in order to achieve high-performance simulations. The integration of diverse biomolecular models needs to convert molecular data between different data representations of different models. This data conversion is often non-trivial, requires extensive human input and is inevitably error prone. In this paper we present an automated data conversion method for biomolecular simulations between molecular dynamics and quantum mechanics/molecular mechanics models. Our approach is developed around an XML data representation called BioSimML (Biomolecular Simulation Markup Language. BioSimML provides a domain specific data representation for biomolecular modelling which can effciently support data interoperability between different biomolecular simulation models and data formats.

  1. Biomolecular Markers in Cancer of the Tongue

    Directory of Open Access Journals (Sweden)

    Daris Ferrari

    2009-01-01

    Full Text Available The incidence of tongue cancer is increasing worldwide, and its aggressiveness remains high regardless of treatment. Genetic changes and the expression of abnormal proteins have been frequently reported in the case of head and neck cancers, but the little information that has been published concerning tongue tumours is often contradictory. This review will concentrate on the immunohistochemical expression of biomolecular markers and their relationships with clinical behaviour and prognosis. Most of these proteins are associated with nodal stage, tumour progression and metastases, but there is still controversy concerning their impact on disease-free and overall survival, and treatment response. More extensive clinical studies are needed to identify the patterns of molecular alterations and the most reliable predictors in order to develop tailored anti-tumour strategies based on the targeting of hypoxia markers, vascular and lymphangiogenic factors, epidermal growth factor receptors, intracytoplasmatic signalling and apoptosis.

  2. Biomolecular simulations on petascale: promises and challenges

    International Nuclear Information System (INIS)

    Agarwal, Pratul K; Alam, Sadaf R

    2006-01-01

    Proteins work as highly efficient machines at the molecular level and are responsible for a variety of processes in all living cells. There is wide interest in understanding these machines for implications in biochemical/biotechnology industries as well as in health related fields. Over the last century, investigations of proteins based on a variety of experimental techniques have provided a wealth of information. More recently, theoretical and computational modeling using large scale simulations is providing novel insights into the functioning of these machines. The next generation supercomputers with petascale computing power, hold great promises as well as challenges for the biomolecular simulation scientists. We briefly discuss the progress being made in this area

  3. Micro- and nanodevices integrated with biomolecular probes.

    Science.gov (United States)

    Alapan, Yunus; Icoz, Kutay; Gurkan, Umut A

    2015-12-01

    Understanding how biomolecules, proteins and cells interact with their surroundings and other biological entities has become the fundamental design criterion for most biomedical micro- and nanodevices. Advances in biology, medicine, and nanofabrication technologies complement each other and allow us to engineer new tools based on biomolecules utilized as probes. Engineered micro/nanosystems and biomolecules in nature have remarkably robust compatibility in terms of function, size, and physical properties. This article presents the state of the art in micro- and nanoscale devices designed and fabricated with biomolecular probes as their vital constituents. General design and fabrication concepts are presented and three major platform technologies are highlighted: microcantilevers, micro/nanopillars, and microfluidics. Overview of each technology, typical fabrication details, and application areas are presented by emphasizing significant achievements, current challenges, and future opportunities. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Modified-hybrid optical neural network filter for multiple object recognition within cluttered scenes

    Science.gov (United States)

    Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.

    2009-08-01

    Motivated by the non-linear interpolation and generalization abilities of the hybrid optical neural network filter between the reference and non-reference images of the true-class object we designed the modifiedhybrid optical neural network filter. We applied an optical mask to the hybrid optical neural network's filter input. The mask was built with the constant weight connections of a randomly chosen image included in the training set. The resulted design of the modified-hybrid optical neural network filter is optimized for performing best in cluttered scenes of the true-class object. Due to the shift invariance properties inherited by its correlator unit the filter can accommodate multiple objects of the same class to be detected within an input cluttered image. Additionally, the architecture of the neural network unit of the general hybrid optical neural network filter allows the recognition of multiple objects of different classes within the input cluttered image by modifying the output layer of the unit. We test the modified-hybrid optical neural network filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. The filter is shown to exhibit with a single pass over the input data simultaneously out-of-plane rotation, shift invariance and good clutter tolerance. It is able to successfully detect and classify correctly the true-class objects within background clutter for which there has been no previous training.

  5. Fast Construction of Near Parsimonious Hybridization Networks for Multiple Phylogenetic Trees.

    Science.gov (United States)

    Mirzaei, Sajad; Wu, Yufeng

    2016-01-01

    Hybridization networks represent plausible evolutionary histories of species that are affected by reticulate evolutionary processes. An established computational problem on hybridization networks is constructing the most parsimonious hybridization network such that each of the given phylogenetic trees (called gene trees) is "displayed" in the network. There have been several previous approaches, including an exact method and several heuristics, for this NP-hard problem. However, the exact method is only applicable to a limited range of data, and heuristic methods can be less accurate and also slow sometimes. In this paper, we develop a new algorithm for constructing near parsimonious networks for multiple binary gene trees. This method is more efficient for large numbers of gene trees than previous heuristics. This new method also produces more parsimonious results on many simulated datasets as well as a real biological dataset than a previous method. We also show that our method produces topologically more accurate networks for many datasets.

  6. Lifetime Optimization of a Multiple Sink Wireless Sensor Network through Energy Balancing

    Directory of Open Access Journals (Sweden)

    Tapan Kumar Jain

    2015-01-01

    Full Text Available The wireless sensor network consists of small limited energy sensors which are connected to one or more sinks. The maximum energy consumption takes place in communicating the data from the nodes to the sink. Multiple sink WSN has an edge over the single sink WSN where very less energy is utilized in sending the data to the sink, as the number of hops is reduced. If the energy consumed by a node is balanced between the other nodes, the lifetime of the network is considerably increased. The network lifetime optimization is achieved by restructuring the network by modifying the neighbor nodes of a sink. Only those nodes are connected to a sink which makes the total energy of the sink less than the threshold. This energy balancing through network restructuring optimizes the network lifetime. This paper depicts this fact through simulations done in MATLAB.

  7. Beamspace Multiple Input Multiple Output. Part II: Steerable Antennas in Mobile Ad Hoc Networks

    Science.gov (United States)

    2016-09-01

    to the transmitter with half the channel transfer function power , since the actual receiver dwells on each channel only half the time. Fourth diagram...steering in a wireless network to maximize signal power and minimize interference [8–10]. The ability to switch beams adds another diversity dimension to...channel transfer function power , since the actual receiver dwells on each channel only half the time. Fourth diagram: The transmit array sends four

  8. Study on multiple-hops performance of MOOC sequences-based optical labels for OPS networks

    Science.gov (United States)

    Zhang, Chongfu; Qiu, Kun; Ma, Chunli

    2009-11-01

    In this paper, we utilize a new study method that is under independent case of multiple optical orthogonal codes to derive the probability function of MOOCS-OPS networks, discuss the performance characteristics for a variety of parameters, and compare some characteristics of the system employed by single optical orthogonal code or multiple optical orthogonal codes sequences-based optical labels. The performance of the system is also calculated, and our results verify that the method is effective. Additionally it is found that performance of MOOCS-OPS networks would, negatively, be worsened, compared with single optical orthogonal code-based optical label for optical packet switching (SOOC-OPS); however, MOOCS-OPS networks can greatly enlarge the scalability of optical packet switching networks.

  9. Augmented lagrange hopfield network for economic dispatch with multiple fuel options

    International Nuclear Information System (INIS)

    Dieu, Vo Ngoc; Ongsakul, Weerakorn; Polprasert, Jirawadee

    2011-01-01

    This paper proposes an augmented Lagrange Hopfield network (ALHN) for solving economic dispatch (ED) problem with multiple fuel options. The proposed ALHN method is a continuous Hopfield neural network with its energy function based on augmented Lagrangian function. The advantages of ALHN over the conventional Hopfield neural network are easier use, more general applications, faster convergence, better optimal solution, and larger scale of problem implementation. The method solves the problem by directly searching the most suitable fuel among the available fuels of each unit and finding the optimal solution for the problem based on minimization of the energy function of the continuous Hopfield neural network. The proposed method is tested on systems up to 100 units and the obtained results are compared to those from other methods in the literature. The results have shown that the proposed method is efficient for solving the ED problem with multiple fuel options and favorable for implementation in large scale problems.

  10. Implementing multiple intervention strategies in Dutch public health-related policy networks.

    Science.gov (United States)

    Harting, Janneke; Peters, Dorothee; Grêaux, Kimberly; van Assema, Patricia; Verweij, Stefan; Stronks, Karien; Klijn, Erik-Hans

    2017-10-13

    Improving public health requires multiple intervention strategies. Implementing such an intervention mix is supposed to require a multisectoral policy network. As evidence to support this assumption is scarce, we examined under which conditions public health-related policy networks were able to implement an intervention mix. Data were collected (2009-14) from 29 Dutch public health policy networks. Surveys were used to identify the number of policy sectors, participation of actors, level of trust, networking by the project leader, and intervention strategies implemented. Conditions sufficient for an intervention mix (≥3 of 4 non-educational strategies present) were determined in a fuzzy-set qualitative comparative analysis. A multisectoral policy network (≥7 of 14 sectors present) was neither a necessary nor a sufficient condition. In multisectoral networks, additionally required was either the active participation of network actors (≥50% actively involved) or active networking by the project leader (≥monthly contacts with network actors). In policy networks that included few sectors, a high level of trust (positive perceptions of each other's intentions) was needed-in the absence though of any of the other conditions. If the network actors were also actively involved, an extra requirement was active networking by the project leader. We conclude that the multisectoral composition of policy networks can contribute to the implementation of a variety of intervention strategies, but not without additional efforts. However, policy networks that include only few sectors are also able to implement an intervention mix. Here, trust seems to be the most important condition. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  11. Comparison of a Ring On-Chip Network and a Code-Division Multiple-Access On-Chip Network

    Directory of Open Access Journals (Sweden)

    Xin Wang

    2007-01-01

    Full Text Available Two network-on-chip (NoC designs are examined and compared in this paper. One design applies a bidirectional ring connection scheme, while the other design applies a code-division multiple-access (CDMA connection scheme. Both of the designs apply globally asynchronous locally synchronous (GALS scheme in order to deal with the issue of transferring data in a multiple-clock-domain environment of an on-chip system. The two NoC designs are compared with each other by their network structures, data transfer principles, network node structures, and their asynchronous designs. Both the synchronous and the asynchronous designs of the two on-chip networks are realized using a hardware-description language (HDL in order to make the entire designs suit the commonly used synchronous design tools and flow. The performance estimation and comparison of the two NoC designs which are based on the HDL realizations are addressed. By comparing the two NoC designs, the advantages and disadvantages of applying direct connection and CDMA connection schemes in an on-chip communication network are discussed.

  12. Nonadditivity of quantum capacities of quantum multiple-access channels and the butterfly network

    International Nuclear Information System (INIS)

    Huang Peng; He Guangqiang; Zhu Jun; Zeng Guihua

    2011-01-01

    Multipartite quantum information transmission without additional classical resources is investigated. We show purely quantum superadditivity of quantum capacity regions of quantum memoryless multiple-access (MA) channels, which are not entanglement breaking. Also, we find that the superadditivity holds when the MA channel extends to the quantum butterfly network, which can achieve quantum network coding. The present widespread effects for the channels which enable entanglement distribution have not been revealed for multipartite scenarios.

  13. Global exponential stability for reaction-diffusion recurrent neural networks with multiple time varying delays

    International Nuclear Information System (INIS)

    Lou, X.; Cui, B.

    2008-01-01

    In this paper we consider the problem of exponential stability for recurrent neural networks with multiple time varying delays and reaction-diffusion terms. The activation functions are supposed to be bounded and globally Lipschitz continuous. By means of Lyapunov functional, sufficient conditions are derived, which guarantee global exponential stability of the delayed neural network. Finally, a numerical example is given to show the correctness of our analysis. (author)

  14. Adaptive multi-node multiple input and multiple output (MIMO) transmission for mobile wireless multimedia sensor networks.

    Science.gov (United States)

    Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo

    2013-10-02

    Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase.

  15. Robustness Assessment of Urban Road Network with Consideration of Multiple Hazard Events.

    Science.gov (United States)

    Zhou, Yaoming; Sheu, Jiuh-Biing; Wang, Junwei

    2017-08-01

    Robustness measures a system's ability of being insensitive to disturbances. Previous studies assessed the robustness of transportation networks to a single disturbance without considering simultaneously happening multiple events. The purpose of this article is to address this problem and propose a new framework to assess the robustness of an urban transportation network. The framework consists of two layers. The upper layer is to define the robustness index based on the impact evaluation in different scenarios obtained from the lower layer, whereas the lower layer is to evaluate the performance of each hypothetical disrupted road network given by the upper layer. The upper layer has two varieties, that is, robustness against random failure and robustness against intentional attacks. This robustness measurement framework is validated by application to a real-world urban road network in Hong Kong. The results show that the robustness of a transport network with consideration of multiple events is quite different from and more comprehensive than that with consideration of only a single disruption. We also propose a Monte Carlo method and a heuristic algorithm to handle different scenarios with multiple hazard events, which is proved to be quite efficient. This methodology can also be applied to conduct risk analysis of other systems where multiple failures or disruptions exist. © 2017 Society for Risk Analysis.

  16. Multivariate Multiple Regression Models for a Big Data-Empowered SON Framework in Mobile Wireless Networks

    Directory of Open Access Journals (Sweden)

    Yoonsu Shin

    2016-01-01

    Full Text Available In the 5G era, the operational cost of mobile wireless networks will significantly increase. Further, massive network capacity and zero latency will be needed because everything will be connected to mobile networks. Thus, self-organizing networks (SON are needed, which expedite automatic operation of mobile wireless networks, but have challenges to satisfy the 5G requirements. Therefore, researchers have proposed a framework to empower SON using big data. The recent framework of a big data-empowered SON analyzes the relationship between key performance indicators (KPIs and related network parameters (NPs using machine-learning tools, and it develops regression models using a Gaussian process with those parameters. The problem, however, is that the methods of finding the NPs related to the KPIs differ individually. Moreover, the Gaussian process regression model cannot determine the relationship between a KPI and its various related NPs. In this paper, to solve these problems, we proposed multivariate multiple regression models to determine the relationship between various KPIs and NPs. If we assume one KPI and multiple NPs as one set, the proposed models help us process multiple sets at one time. Also, we can find out whether some KPIs are conflicting or not. We implement the proposed models using MapReduce.

  17. Performance analysis of quantum access network using code division multiple access model

    International Nuclear Information System (INIS)

    Hu Linxi; Yang Can; He Guangqiang

    2017-01-01

    A quantum access network has been implemented by frequency division multiple access and time division multiple access, while code division multiple access is limited for its difficulty to realize the orthogonality of the code. Recently, the chaotic phase shifters were proposed to guarantee the orthogonality by different chaotic signals and spread the spectral content of the quantum states. In this letter, we propose to implement the code division multiple access quantum network by using chaotic phase shifters and synchronization. Due to the orthogonality of the different chaotic phase shifter, every pair of users can faithfully transmit quantum information through a common channel and have little crosstalk between different users. Meanwhile, the broadband spectra of chaotic signals efficiently help the quantum states to defend against channel loss and noise. (paper)

  18. A Multiple Mobility Support Approach (MMSA Based on PEAS for NCW in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Bong-Joo Koo

    2011-01-01

    Full Text Available Wireless Sensor Networks (WSNs can be implemented as one of sensor systems in Network Centric Warfare (NCW. Mobility support and energy efficiency are key concerns for this application, due to multiple mobile users and stimuli in real combat field. However, mobility support approaches that can be adopted in this circumstance are rare. This paper proposes Multiple Mobility Support Approach (MMSA based on Probing Environment and Adaptive Sleeping (PEAS to support the simultaneous mobility of both multiple users and stimuli by sharing the information of stimuli in WSNs. Simulations using Qualnet are conducted, showing that MMSA can support multiple mobile users and stimuli with good energy efficiency. It is expected that the proposed MMSA can be applied to real combat field.

  19. DNA algorithms of implementing biomolecular databases on a biological computer.

    Science.gov (United States)

    Chang, Weng-Long; Vasilakos, Athanasios V

    2015-01-01

    In this paper, DNA algorithms are proposed to perform eight operations of relational algebra (calculus), which include Cartesian product, union, set difference, selection, projection, intersection, join, and division, on biomolecular relational databases.

  20. Network Events on Multiple Space and Time Scales in Cultured Neural Networks and in a Stochastic Rate Model.

    Directory of Open Access Journals (Sweden)

    Guido Gigante

    2015-11-01

    Full Text Available Cortical networks, in-vitro as well as in-vivo, can spontaneously generate a variety of collective dynamical events such as network spikes, UP and DOWN states, global oscillations, and avalanches. Though each of them has been variously recognized in previous works as expression of the excitability of the cortical tissue and the associated nonlinear dynamics, a unified picture of the determinant factors (dynamical and architectural is desirable and not yet available. Progress has also been partially hindered by the use of a variety of statistical measures to define the network events of interest. We propose here a common probabilistic definition of network events that, applied to the firing activity of cultured neural networks, highlights the co-occurrence of network spikes, power-law distributed avalanches, and exponentially distributed 'quasi-orbits', which offer a third type of collective behavior. A rate model, including synaptic excitation and inhibition with no imposed topology, synaptic short-term depression, and finite-size noise, accounts for all these different, coexisting phenomena. We find that their emergence is largely regulated by the proximity to an oscillatory instability of the dynamics, where the non-linear excitable behavior leads to a self-amplification of activity fluctuations over a wide range of scales in space and time. In this sense, the cultured network dynamics is compatible with an excitation-inhibition balance corresponding to a slightly sub-critical regime. Finally, we propose and test a method to infer the characteristic time of the fatigue process, from the observed time course of the network's firing rate. Unlike the model, possessing a single fatigue mechanism, the cultured network appears to show multiple time scales, signalling the possible coexistence of different fatigue mechanisms.

  1. Lower Bounds on the Maximum Energy Benefit of Network Coding for Wireless Multiple Unicast

    Directory of Open Access Journals (Sweden)

    Matsumoto Ryutaroh

    2010-01-01

    Full Text Available We consider the energy savings that can be obtained by employing network coding instead of plain routing in wireless multiple unicast problems. We establish lower bounds on the benefit of network coding, defined as the maximum of the ratio of the minimum energy required by routing and network coding solutions, where the maximum is over all configurations. It is shown that if coding and routing solutions are using the same transmission range, the benefit in d-dimensional networks is at least . Moreover, it is shown that if the transmission range can be optimized for routing and coding individually, the benefit in 2-dimensional networks is at least 3. Our results imply that codes following a decode-and-recombine strategy are not always optimal regarding energy efficiency.

  2. An energy efficient distance-aware routing algorithm with multiple mobile sinks for wireless sensor networks.

    Science.gov (United States)

    Wang, Jin; Li, Bin; Xia, Feng; Kim, Chang-Seob; Kim, Jeong-Uk

    2014-08-18

    Traffic patterns in wireless sensor networks (WSNs) usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption.

  3. An Energy Efficient Distance-Aware Routing Algorithm with Multiple Mobile Sinks for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jin Wang

    2014-08-01

    Full Text Available Traffic patterns in wireless sensor networks (WSNs usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption.

  4. A fast mollified impulse method for biomolecular atomistic simulations

    Energy Technology Data Exchange (ETDEWEB)

    Fath, L., E-mail: lukas.fath@kit.edu [Institute for App. and Num. Mathematics, Karlsruhe Institute of Technology (Germany); Hochbruck, M., E-mail: marlis.hochbruck@kit.edu [Institute for App. and Num. Mathematics, Karlsruhe Institute of Technology (Germany); Singh, C.V., E-mail: chandraveer.singh@utoronto.ca [Department of Materials Science & Engineering, University of Toronto (Canada)

    2017-03-15

    Classical integration methods for molecular dynamics are inherently limited due to resonance phenomena occurring at certain time-step sizes. The mollified impulse method can partially avoid this problem by using appropriate filters based on averaging or projection techniques. However, existing filters are computationally expensive and tedious in implementation since they require either analytical Hessians or they need to solve nonlinear systems from constraints. In this work we follow a different approach based on corotation for the construction of a new filter for (flexible) biomolecular simulations. The main advantages of the proposed filter are its excellent stability properties and ease of implementation in standard softwares without Hessians or solving constraint systems. By simulating multiple realistic examples such as peptide, protein, ice equilibrium and ice–ice friction, the new filter is shown to speed up the computations of long-range interactions by approximately 20%. The proposed filtered integrators allow step sizes as large as 10 fs while keeping the energy drift less than 1% on a 50 ps simulation.

  5. Biomolecular surface construction by PDE transform.

    Science.gov (United States)

    Zheng, Qiong; Yang, Siyang; Wei, Guo-Wei

    2012-03-01

    This work proposes a new framework for the surface generation based on the partial differential equation (PDE) transform. The PDE transform has recently been introduced as a general approach for the mode decomposition of images, signals, and data. It relies on the use of arbitrarily high-order PDEs to achieve the time-frequency localization, control the spectral distribution, and regulate the spatial resolution. The present work provides a new variational derivation of high-order PDE transforms. The fast Fourier transform is utilized to accomplish the PDE transform so as to avoid stringent stability constraints in solving high-order PDEs. As a consequence, the time integration of high-order PDEs can be done efficiently with the fast Fourier transform. The present approach is validated with a variety of test examples in two-dimensional and three-dimensional settings. We explore the impact of the PDE transform parameters, such as the PDE order and propagation time, on the quality of resulting surfaces. Additionally, we utilize a set of 10 proteins to compare the computational efficiency of the present surface generation method and a standard approach in Cartesian meshes. Moreover, we analyze the present method by examining some benchmark indicators of biomolecular surface, that is, surface area, surface-enclosed volume, solvation free energy, and surface electrostatic potential. A test set of 13 protein molecules is used in the present investigation. The electrostatic analysis is carried out via the Poisson-Boltzmann equation model. To further demonstrate the utility of the present PDE transform-based surface method, we solve the Poisson-Nernst-Planck equations with a PDE transform surface of a protein. Second-order convergence is observed for the electrostatic potential and concentrations. Finally, to test the capability and efficiency of the present PDE transform-based surface generation method, we apply it to the construction of an excessively large biomolecule, a

  6. Multiscale Persistent Functions for Biomolecular Structure Characterization

    Energy Technology Data Exchange (ETDEWEB)

    Xia, Kelin [Nanyang Technological University (Singapore). Division of Mathematical Sciences, School of Physical, Mathematical Sciences and School of Biological Sciences; Li, Zhiming [Central China Normal University, Wuhan (China). Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics; Mu, Lin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division

    2017-11-02

    Here in this paper, we introduce multiscale persistent functions for biomolecular structure characterization. The essential idea is to combine our multiscale rigidity functions (MRFs) with persistent homology analysis, so as to construct a series of multiscale persistent functions, particularly multiscale persistent entropies, for structure characterization. To clarify the fundamental idea of our method, the multiscale persistent entropy (MPE) model is discussed in great detail. Mathematically, unlike the previous persistent entropy (Chintakunta et al. in Pattern Recognit 48(2):391–401, 2015; Merelli et al. in Entropy 17(10):6872–6892, 2015; Rucco et al. in: Proceedings of ECCS 2014, Springer, pp 117–128, 2016), a special resolution parameter is incorporated into our model. Various scales can be achieved by tuning its value. Physically, our MPE can be used in conformational entropy evaluation. More specifically, it is found that our method incorporates in it a natural classification scheme. This is achieved through a density filtration of an MRF built from angular distributions. To further validate our model, a systematical comparison with the traditional entropy evaluation model is done. Additionally, it is found that our model is able to preserve the intrinsic topological features of biomolecular data much better than traditional approaches, particularly for resolutions in the intermediate range. Moreover, by comparing with traditional entropies from various grid sizes, bond angle-based methods and a persistent homology-based support vector machine method (Cang et al. in Mol Based Math Biol 3:140–162, 2015), we find that our MPE method gives the best results in terms of average true positive rate in a classic protein structure classification test. More interestingly, all-alpha and all-beta protein classes can be clearly separated from each other with zero error only in our model. Finally, a special protein structure index (PSI) is proposed, for the first

  7. Partial Interference and Its Performance Impact on Wireless Multiple Access Networks

    Directory of Open Access Journals (Sweden)

    Lau WingCheong

    2010-01-01

    Full Text Available To determine the capacity of wireless multiple access networks, the interference among the wireless links must be accurately modeled. In this paper, we formalize the notion of the partial interference phenomenon observed in many recent wireless measurement studies and establish analytical models with tractable solutions for various types of wireless multiple access networks. In particular, we characterize the stability region of IEEE 802.11 networks under partial interference with two potentially unsaturated links numerically. We also provide a closed-form solution for the stability region of slotted ALOHA networks under partial interference with two potentially unsaturated links and obtain a partial characterization of the boundary of the stability region for the general M-link case. Finally, we derive a closed-form approximated solution for the stability region for general M-link slotted ALOHA system under partial interference effects. Based on our results, we demonstrate that it is important to model the partial interference effects while analyzing wireless multiple access networks. This is because such considerations can result in not only significant quantitative differences in the predicted system capacity but also fundamental qualitative changes in the shape of the stability region of the systems.

  8. Report from the European myeloma network on interphase FISH in multiple myeloma and related disorders

    NARCIS (Netherlands)

    F. Ross (F.); H. Avet-Loiseau; G. Ameye (Geneviève); N. Gutierrez (Norma); G. Liebisch (Gerhard); S. O'Connor (Sheila); K. Dalva (Klara); F. Fabris (Federica Margherita); A.M. Testi (Adele); M. Jarosova (M.); C. Hodkinson (Clare); A. Collin (Anna); G. Kerndrup (Gitte); P. Kuglik (Petr); D. Ladon (Dariusz); P. Bernasconi (Paolo); B. Maes (Bart); Z. Zemanova (Zuzana); K. Michalova (Kyra); L. Michau (Lucienne); K. Neben (Kai); N.E.U. Hermansen (N. Emil); K. Rack (Katrina); A. Rocci (Alberto); R. Protheroe (Rebecca); L. Chiecchio (Laura); H.A. Poirel (Hélène A); P. Sonneveld (Pieter); M. Nyegaard (M.); H.E. Johnsen (Hans)

    2012-01-01

    textabstractThe European Myeloma Network has organized two workshops on fluorescence in situ hybridization in multiple myeloma. The first aimed to identify specific indications and consensus technical approaches of current practice. A second workshop followed a quality control exercise in which 21

  9. Multiple Distributed Smart Microgrids with a Self-Autonomous, Energy Harvesting Wireless Sensor Network

    DEFF Research Database (Denmark)

    Guerrero, Josep M.; Kheng Tan, Yen

    2012-01-01

    The chapter covers the smart wireless sensors for microgrids, as well as the energy harvesting technology used to sustain the operations of these sensors. Last, a case study on the multiple distributed smart microgrids with a self-autonomous, energy harvesting wireless sensor network is presented....

  10. Multiple-state based power control for multi-radio multi-channel wireless mesh networks

    CSIR Research Space (South Africa)

    Olwal, TO

    2009-01-01

    Full Text Available Multi-Radio Multi-Channel (MRMC) systems are key to power control problems in wireless mesh networks (WMNs). In this paper, we present asynchronous multiple-state based power control for MRMC WMNs. First, WMN is represented as a set of disjoint...

  11. Featuring Multiple Local Optima to Assist the User in the Interpretation of Induced Bayesian Network Models

    DEFF Research Database (Denmark)

    Dalgaard, Jens; Pena, Jose; Kocka, Tomas

    2004-01-01

    We propose a method to assist the user in the interpretation of the best Bayesian network model indu- ced from data. The method consists in extracting relevant features from the model (e.g. edges, directed paths and Markov blankets) and, then, assessing the con¯dence in them by studying multiple...

  12. Knowledge-Based Multiple Access Protocol in Broadband Wireless ATM Networks

    DEFF Research Database (Denmark)

    Liu, Hong; Gliese, Ulrik Bo; Dittmann, Lars

    1999-01-01

    In this paper, we propose a knowledge-based multiple access protocol for the extension of wireline ATM to wireless networks. The objective is to enable effecient transmission of all kinds of ATM traffic in the wireless channel with guaranteed QoS.The proposed protocol utilixes knowledge of the main...... guaranteed QoS requirements to a variety of ATM applications....

  13. Exploiting deep neural networks and head movements for binaural localisation of multiple speakers in reverberant conditions

    DEFF Research Database (Denmark)

    Ma, Ning; Brown, Guy J.; May, Tobias

    2015-01-01

    This paper presents a novel machine-hearing system that exploits deep neural networks (DNNs) and head movements for binaural localisation of multiple speakers in reverberant conditions. DNNs are used to map binaural features, consisting of the complete crosscorrelation function (CCF) and interaural...

  14. Disruption of Structural and Functional Networks in Long-Standing Multiple Sclerosis

    NARCIS (Netherlands)

    Tewarie, P.; Steenwijk, M.D.; Tijms, B.M.; Daams, M.; Balk, L.J.; Stam, C.J.; Uitdehaag, B.M.J.; Polman, C.H.; Geurts, J.J.G.; Barkhof, F.; Pouwels, P.J.W.; Vrenken, H.; Hillebrand, A.

    2014-01-01

    Both gray matter atrophy and disruption of functional networks are important predictors for physical disability and cognitive impairment in multiple sclerosis (MS), yet their relationship is poorly understood. Graph theory provides a modality invariant framework to analyze patterns of gray matter

  15. Robustness analysis of uncertain dynamical neural networks with multiple time delays.

    Science.gov (United States)

    Senan, Sibel

    2015-10-01

    This paper studies the problem of global robust asymptotic stability of the equilibrium point for the class of dynamical neural networks with multiple time delays with respect to the class of slope-bounded activation functions and in the presence of the uncertainties of system parameters of the considered neural network model. By using an appropriate Lyapunov functional and exploiting the properties of the homeomorphism mapping theorem, we derive a new sufficient condition for the existence, uniqueness and global robust asymptotic stability of the equilibrium point for the class of neural networks with multiple time delays. The obtained stability condition basically relies on testing some relationships imposed on the interconnection matrices of the neural system, which can be easily verified by using some certain properties of matrices. An instructive numerical example is also given to illustrate the applicability of our result and show the advantages of this new condition over the previously reported corresponding results. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Performance of an opportunistic multi-user cognitive network with multiple primary users

    KAUST Repository

    Khan, Fahd Ahmed

    2014-04-01

    Consider a multi-user underlay cognitive network where multiple cognitive users, having limited peak transmit power, concurrently share the spectrum with a primary network with multiple users. The channel between the secondary network is assumed to have independent but not identical Nakagami-m fading. The interference channel between the secondary users and the primary users is assumed to have Rayleigh fading. The uplink scenario is considered where a single secondary user is selected for transmission. This opportunistic selection depends on the transmission channel power gain and the interference channel power gain as well as the power allocation policy adopted at the users. Exact closed form expressions for the momentgenerating function, outage performance and the symbol-error-rate performance are derived. The outage performance is also studied in the asymptotic regimes and the generalized diversity gain of this scheduling scheme is derived. Numerical results corroborate the derived analytical results.

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

    Science.gov (United States)

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

    2016-11-30

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

  18. DETECTION AND LOCALIZATION OF MULTIPLE SPOOFING ATTACKERS FOR MOBILE WIRELESS NETWORKS

    Directory of Open Access Journals (Sweden)

    R. Maivizhi

    2015-06-01

    Full Text Available The openness nature of wireless networks allows adversaries to easily launch variety of spoofing attacks and causes havoc in network performance. Recent approaches used Received Signal Strength (RSS traces, which only detect spoofing attacks in mobile wireless networks. However, it is not always desirable to use these methods as RSS values fluctuate significantly over time due to distance, noise and interference. In this paper, we discusses a novel approach, Mobile spOofing attack DEtection and Localization in WIireless Networks (MODELWIN system, which exploits location information about nodes to detect identity-based spoofing attacks in mobile wireless networks. Also, this approach determines the number of attackers who used the same node identity to masquerade as legitimate device. Moreover, multiple adversaries can be localized accurately. By eliminating attackers the proposed system enhances network performance. We have evaluated our technique through simulation using an 802.11 (WiFi network and an 802.15.4 (Zigbee networks. The results prove that MODELWIN can detect spoofing attacks with a very high detection rate and localize adversaries accurately.

  19. A Context-Aware Adaptive Streaming Media Distribution System in a Heterogeneous Network with Multiple Terminals

    Directory of Open Access Journals (Sweden)

    Yepeng Ni

    2016-01-01

    Full Text Available We consider the problem of streaming media transmission in a heterogeneous network from a multisource server to home multiple terminals. In wired network, the transmission performance is limited by network state (e.g., the bandwidth variation, jitter, and packet loss. In wireless network, the multiple user terminals can cause bandwidth competition. Thus, the streaming media distribution in a heterogeneous network becomes a severe challenge which is critical for QoS guarantee. In this paper, we propose a context-aware adaptive streaming media distribution system (CAASS, which implements the context-aware module to perceive the environment parameters and use the strategy analysis (SA module to deduce the most suitable service level. This approach is able to improve the video quality for guarantying streaming QoS. We formulate the optimization problem of QoS relationship with the environment parameters based on the QoS testing algorithm for IPTV in ITU-T G.1070. We evaluate the performance of the proposed CAASS through 12 types of experimental environments using a prototype system. Experimental results show that CAASS can dynamically adjust the service level according to the environment variation (e.g., network state and terminal performances and outperforms the existing streaming approaches in adaptive streaming media distribution according to peak signal-to-noise ratio (PSNR.

  20. Multiple synchronization transitions in scale-free neuronal networks with electrical and chemical hybrid synapses

    International Nuclear Information System (INIS)

    Liu, Chen; Wang, Jiang; Wang, Lin; Yu, Haitao; Deng, Bin; Wei, Xile; Tsang, Kaiming; Chan, Wailok

    2014-01-01

    Highlights: • Synchronization transitions in hybrid scale-free neuronal networks are investigated. • Multiple synchronization transitions can be induced by the time delay. • Effect of synchronization transitions depends on the ratio of the electrical and chemical synapses. • Coupling strength and the density of inter-neuronal links can enhance the synchronization. -- Abstract: The impacts of information transmission delay on the synchronization transitions in scale-free neuronal networks with electrical and chemical hybrid synapses are investigated. Numerical results show that multiple appearances of synchronization regions transitions can be induced by different information transmission delays. With the time delay increasing, the synchronization of neuronal activities can be enhanced or destroyed, irrespective of the probability of chemical synapses in the whole hybrid neuronal network. In particular, for larger probability of electrical synapses, the regions of synchronous activities appear broader with stronger synchronization ability of electrical synapses compared with chemical ones. Moreover, it can be found that increasing the coupling strength can promote synchronization monotonously, playing the similar role of the increasing the probability of the electrical synapses. Interestingly, the structures and parameters of the scale-free neuronal networks, especially the structural evolvement plays a more subtle role in the synchronization transitions. In the network formation process, it is found that every new vertex is attached to the more old vertices already present in the network, the more synchronous activities will be emerge

  1. Integrated Spintronic Platforms for Biomolecular Recognition Detection

    Science.gov (United States)

    Martins, V. C.; Cardoso, F. A.; Loureiro, J.; Mercier, M.; Germano, J.; Cardoso, S.; Ferreira, R.; Fonseca, L. P.; Sousa, L.; Piedade, M. S.; Freitas, P. P.

    2008-06-01

    This paper covers recent developments in magnetoresistive based biochip platforms fabricated at INESC-MN, and their application to the detection and quantification of pathogenic waterborn microorganisms in water samples for human consumption. Such platforms are intended to give response to the increasing concern related to microbial contaminated water sources. The presented results concern the development of biological active DNA chips and protein chips and the demonstration of the detection capability of the present platforms. Two platforms are described, one including spintronic sensors only (spin-valve based or magnetic tunnel junction based), and the other, a fully scalable platform where each probe site consists of a MTJ in series with a thin film diode (TFD). Two microfluidic systems are described, for cell separation and concentration, and finally, the read out and control integrated electronics are described, allowing the realization of bioassays with a portable point of care unit. The present platforms already allow the detection of complementary biomolecular target recognition with 1 pM concentration.

  2. A multiscale modeling approach for biomolecular systems

    Energy Technology Data Exchange (ETDEWEB)

    Bowling, Alan, E-mail: bowling@uta.edu; Haghshenas-Jaryani, Mahdi, E-mail: mahdi.haghshenasjaryani@mavs.uta.edu [The University of Texas at Arlington, Department of Mechanical and Aerospace Engineering (United States)

    2015-04-15

    This paper presents a new multiscale molecular dynamic model for investigating the effects of external interactions, such as contact and impact, during stepping and docking of motor proteins and other biomolecular systems. The model retains the mass properties ensuring that the result satisfies Newton’s second law. This idea is presented using a simple particle model to facilitate discussion of the rigid body model; however, the particle model does provide insights into particle dynamics at the nanoscale. The resulting three-dimensional model predicts a significant decrease in the effect of the random forces associated with Brownian motion. This conclusion runs contrary to the widely accepted notion that the motor protein’s movements are primarily the result of thermal effects. This work focuses on the mechanical aspects of protein locomotion; the effect ATP hydrolysis is estimated as internal forces acting on the mechanical model. In addition, the proposed model can be numerically integrated in a reasonable amount of time. Herein, the differences between the motion predicted by the old and new modeling approaches are compared using a simplified model of myosin V.

  3. Multiple Spatial Coherence Resonances and Spatial Patterns in a Noise-Driven Heterogeneous Neuronal Network

    Science.gov (United States)

    Li, Yu-Ye; Ding, Xue-Li

    2014-12-01

    Heterogeneity of the neurons and noise are inevitable in the real neuronal network. In this paper, Gaussian white noise induced spatial patterns including spiral waves and multiple spatial coherence resonances are studied in a network composed of Morris—Lecar neurons with heterogeneity characterized by parameter diversity. The relationship between the resonances and the transitions between ordered spiral waves and disordered spatial patterns are achieved. When parameter diversity is introduced, the maxima of multiple resonances increases first, and then decreases as diversity strength increases, which implies that the coherence degrees induced by noise are enhanced at an intermediate diversity strength. The synchronization degree of spatial patterns including ordered spiral waves and disordered patterns is identified to be a very low level. The results suggest that the nervous system can profit from both heterogeneity and noise, and the multiple spatial coherence resonances are achieved via the emergency of spiral waves instead of synchronization patterns.

  4. Multiple Spatial Coherence Resonances and Spatial Patterns in a Noise-Driven Heterogeneous Neuronal Network

    International Nuclear Information System (INIS)

    Li Yu-Ye; Ding Xue-Li

    2014-01-01

    Heterogeneity of the neurons and noise are inevitable in the real neuronal network. In this paper, Gaussian white noise induced spatial patterns including spiral waves and multiple spatial coherence resonances are studied in a network composed of Morris—Lecar neurons with heterogeneity characterized by parameter diversity. The relationship between the resonances and the transitions between ordered spiral waves and disordered spatial patterns are achieved. When parameter diversity is introduced, the maxima of multiple resonances increases first, and then decreases as diversity strength increases, which implies that the coherence degrees induced by noise are enhanced at an intermediate diversity strength. The synchronization degree of spatial patterns including ordered spiral waves and disordered patterns is identified to be a very low level. The results suggest that the nervous system can profit from both heterogeneity and noise, and the multiple spatial coherence resonances are achieved via the emergency of spiral waves instead of synchronization patterns. (interdisciplinary physics and related areas of science and technology)

  5. Spiral Waves and Multiple Spatial Coherence Resonances Induced by Colored Noise in Neuronal Network

    International Nuclear Information System (INIS)

    Tang Zhao; Li Yuye; Xi Lei; Jia Bing; Gu Huaguang

    2012-01-01

    Gaussian colored noise induced spatial patterns and spatial coherence resonances in a square lattice neuronal network composed of Morris-Lecar neurons are studied. Each neuron is at resting state near a saddle-node bifurcation on invariant circle, coupled to its nearest neighbors by electronic coupling. Spiral waves with different structures and disordered spatial structures can be alternately induced within a large range of noise intensity. By calculating spatial structure function and signal-to-noise ratio (SNR), it is found that SNR values are higher when the spiral structures are simple and are lower when the spatial patterns are complex or disordered, respectively. SNR manifest multiple local maximal peaks, indicating that the colored noise can induce multiple spatial coherence resonances. The maximal SNR values decrease as the correlation time of the noise increases. These results not only provide an example of multiple resonances, but also show that Gaussian colored noise play constructive roles in neuronal network. (general)

  6. 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

  7. Prediction Approach of Critical Node Based on Multiple Attribute Decision Making for Opportunistic Sensor Networks

    Directory of Open Access Journals (Sweden)

    Qifan Chen

    2016-01-01

    Full Text Available Predicting critical nodes of Opportunistic Sensor Network (OSN can help us not only to improve network performance but also to decrease the cost in network maintenance. However, existing ways of predicting critical nodes in static network are not suitable for OSN. In this paper, the conceptions of critical nodes, region contribution, and cut-vertex in multiregion OSN are defined. We propose an approach to predict critical node for OSN, which is based on multiple attribute decision making (MADM. It takes RC to present the dependence of regions on Ferry nodes. TOPSIS algorithm is employed to find out Ferry node with maximum comprehensive contribution, which is a critical node. The experimental results show that, in different scenarios, this approach can predict the critical nodes of OSN better.

  8. An energy efficient multiple mobile sinks based routing algorithm for wireless sensor networks

    Science.gov (United States)

    Zhong, Peijun; Ruan, Feng

    2018-03-01

    With the fast development of wireless sensor networks (WSNs), more and more energy efficient routing algorithms have been proposed. However, one of the research challenges is how to alleviate the hot spot problem since nodes close to static sink (or base station) tend to die earlier than other sensors. The introduction of mobile sink node can effectively alleviate this problem since sink node can move along certain trajectories, causing hot spot nodes more evenly distributed. In this paper, we mainly study the energy efficient routing method with multiple mobile sinks support. We divide the whole network into several clusters and study the influence of mobile sink number on network lifetime. Simulation results show that the best network performance appears when mobile sink number is about 3 under our simulation environment.

  9. DMP: Detouring Using Multiple Paths against Jamming Attack for Ubiquitous Networking System

    Directory of Open Access Journals (Sweden)

    Mihui Kim

    2010-04-01

    Full Text Available To successfully realize the ubiquitous network environment including home automation or industrial control systems, it is important to be able to resist a jamming attack. This has recently been considered as an extremely threatening attack because it can collapse the entire network, despite the existence of basic security protocols such as encryption and authentication. In this paper, we present a method of jamming attack tolerant routing using multiple paths based on zones. The proposed scheme divides the network into zones, and manages the candidate forward nodes of neighbor zones. After detecting an attack, detour nodes decide zones for rerouting, and detour packets destined for victim nodes through forward nodes in the decided zones. Simulation results show that our scheme increases the PDR (Packet Delivery Ratio and decreases the delay significantly in comparison with rerouting by a general routing protocol on sensor networks, AODV (Ad hoc On Demand Distance Vector, and a conventional JAM (Jammed Area Mapping service with one reroute.

  10. DMP: detouring using multiple paths against jamming attack for ubiquitous networking system.

    Science.gov (United States)

    Kim, Mihui; Chae, Kijoon

    2010-01-01

    To successfully realize the ubiquitous network environment including home automation or industrial control systems, it is important to be able to resist a jamming attack. This has recently been considered as an extremely threatening attack because it can collapse the entire network, despite the existence of basic security protocols such as encryption and authentication. In this paper, we present a method of jamming attack tolerant routing using multiple paths based on zones. The proposed scheme divides the network into zones, and manages the candidate forward nodes of neighbor zones. After detecting an attack, detour nodes decide zones for rerouting, and detour packets destined for victim nodes through forward nodes in the decided zones. Simulation results show that our scheme increases the PDR (Packet Delivery Ratio) and decreases the delay significantly in comparison with rerouting by a general routing protocol on sensor networks, AODV (Ad hoc On Demand Distance Vector), and a conventional JAM (Jammed Area Mapping) service with one reroute.

  11. ODMBP: Behavior Forwarding for Multiple Property Destinations in Mobile Social Networks

    Directory of Open Access Journals (Sweden)

    Jia Xu

    2016-01-01

    Full Text Available The smartphones are widely available in recent years. Wireless networks and personalized mobile devices are deeply integrated and embedded in our lives. The behavior based forwarding has become a new transmission paradigm for supporting many novel applications. However, the commodities, services, and individuals usually have multiple properties of their interests and behaviors. In this paper, we profile these multiple properties and propose an Opportunistic Dissemination Protocol based on Multiple Behavior Profile, ODMBP, in mobile social networks. We first map the interest space to the behavior space and extract the multiple behavior profiles from the behavior space. Then, we propose the correlation computing model based on the principle of BM25 to calculate the correlation metric of multiple behavior profiles. The correlation metric is used to forward the message to the users who are more similar to the target in our protocol. ODMBP consists of three stages: user initialization, gradient ascent, and group spread. Through extensive simulations, we demonstrate that the proposed multiple behavior profile and correlation computing model are correct and efficient. Compared to other classical routing protocols, ODMBP can significantly improve the performance in the aspect of delivery ratio, delay, and overhead ratio.

  12. Single or multiple synchronization transitions in scale-free neuronal networks with electrical or chemical coupling

    International Nuclear Information System (INIS)

    Hao Yinghang; Gong, Yubing; Wang Li; Ma Xiaoguang; Yang Chuanlu

    2011-01-01

    Research highlights: → Single synchronization transition for gap-junctional coupling. → Multiple synchronization transitions for chemical synaptic coupling. → Gap junctions and chemical synapses have different impacts on synchronization transition. → Chemical synapses may play a dominant role in neurons' information processing. - Abstract: In this paper, we have studied time delay- and coupling strength-induced synchronization transitions in scale-free modified Hodgkin-Huxley (MHH) neuron networks with gap-junctions and chemical synaptic coupling. It is shown that the synchronization transitions are much different for these two coupling types. For gap-junctions, the neurons exhibit a single synchronization transition with time delay and coupling strength, while for chemical synapses, there are multiple synchronization transitions with time delay, and the synchronization transition with coupling strength is dependent on the time delay lengths. For short delays we observe a single synchronization transition, whereas for long delays the neurons exhibit multiple synchronization transitions as the coupling strength is varied. These results show that gap junctions and chemical synapses have different impacts on the pattern formation and synchronization transitions of the scale-free MHH neuronal networks, and chemical synapses, compared to gap junctions, may play a dominant and more active function in the firing activity of the networks. These findings would be helpful for further understanding the roles of gap junctions and chemical synapses in the firing dynamics of neuronal networks.

  13. Single or multiple synchronization transitions in scale-free neuronal networks with electrical or chemical coupling

    Energy Technology Data Exchange (ETDEWEB)

    Hao Yinghang [School of Physics, Ludong University, Yantai 264025 (China); Gong, Yubing, E-mail: gongyubing09@hotmail.co [School of Physics, Ludong University, Yantai 264025 (China); Wang Li; Ma Xiaoguang; Yang Chuanlu [School of Physics, Ludong University, Yantai 264025 (China)

    2011-04-15

    Research highlights: Single synchronization transition for gap-junctional coupling. Multiple synchronization transitions for chemical synaptic coupling. Gap junctions and chemical synapses have different impacts on synchronization transition. Chemical synapses may play a dominant role in neurons' information processing. - Abstract: In this paper, we have studied time delay- and coupling strength-induced synchronization transitions in scale-free modified Hodgkin-Huxley (MHH) neuron networks with gap-junctions and chemical synaptic coupling. It is shown that the synchronization transitions are much different for these two coupling types. For gap-junctions, the neurons exhibit a single synchronization transition with time delay and coupling strength, while for chemical synapses, there are multiple synchronization transitions with time delay, and the synchronization transition with coupling strength is dependent on the time delay lengths. For short delays we observe a single synchronization transition, whereas for long delays the neurons exhibit multiple synchronization transitions as the coupling strength is varied. These results show that gap junctions and chemical synapses have different impacts on the pattern formation and synchronization transitions of the scale-free MHH neuronal networks, and chemical synapses, compared to gap junctions, may play a dominant and more active function in the firing activity of the networks. These findings would be helpful for further understanding the roles of gap junctions and chemical synapses in the firing dynamics of neuronal networks.

  14. Revealing Pathway Dynamics in Heart Diseases by Analyzing Multiple Differential Networks.

    Directory of Open Access Journals (Sweden)

    Xiaoke Ma

    2015-06-01

    Full Text Available Development of heart diseases is driven by dynamic changes in both the activity and connectivity of gene pathways. Understanding these dynamic events is critical for understanding pathogenic mechanisms and development of effective treatment. Currently, there is a lack of computational methods that enable analysis of multiple gene networks, each of which exhibits differential activity compared to the network of the baseline/healthy condition. We describe the iMDM algorithm to identify both unique and shared gene modules across multiple differential co-expression networks, termed M-DMs (multiple differential modules. We applied iMDM to a time-course RNA-Seq dataset generated using a murine heart failure model generated on two genotypes. We showed that iMDM achieves higher accuracy in inferring gene modules compared to using single or multiple co-expression networks. We found that condition-specific M-DMs exhibit differential activities, mediate different biological processes, and are enriched for genes with known cardiovascular phenotypes. By analyzing M-DMs that are present in multiple conditions, we revealed dynamic changes in pathway activity and connectivity across heart failure conditions. We further showed that module dynamics were correlated with the dynamics of disease phenotypes during the development of heart failure. Thus, pathway dynamics is a powerful measure for understanding pathogenesis. iMDM provides a principled way to dissect the dynamics of gene pathways and its relationship to the dynamics of disease phenotype. With the exponential growth of omics data, our method can aid in generating systems-level insights into disease progression.

  15. Biomolecular ions in superfluid helium nanodroplets

    International Nuclear Information System (INIS)

    Gonzalez Florez, Ana Isabel

    2016-01-01

    The function of a biological molecule is closely related to its structure. As a result, understanding and predicting biomolecular structure has become the focus of an extensive field of research. However, the investigation of molecular structure can be hampered by two main difficulties: the inherent complications that may arise from studying biological molecules in their native environment, and the potential congestion of the experimental results as a consequence of the large number of degrees of freedom present in these molecules. In this work, a new experimental setup has been developed and established in order to overcome the afore mentioned limitations combining structure-sensitive gas-phase methods with superfluid helium droplets. First, biological molecules are ionised and brought into the gas phase, often referred to as a clean-room environment, where the species of interest are isolated from their surroundings and, thus, intermolecular interactions are absent. The mass-to-charge selected biomolecules are then embedded inside clusters of superfluid helium with an equilibrium temperature of ∝0.37 K. As a result, the internal energy of the molecules is lowered, thereby reducing the number of populated quantum states. Finally, the local hydrogen bonding patterns of the molecules are investigated by probing specific vibrational modes using the Fritz Haber Institute's free electron laser as a source of infrared radiation. Although the structure of a wide variety of molecules has been studied making use of the sub-Kelvin environment provided by superfluid helium droplets, the suitability of this method for the investigation of biological molecular ions was still unclear. However, the experimental results presented in this thesis demonstrate the applicability of this experimental approach in order to study the structure of intact, large biomolecular ions and the first vibrational spectrum of the protonated pentapeptide leu-enkephalin embedded in helium

  16. Biomolecular ions in superfluid helium nanodroplets

    Energy Technology Data Exchange (ETDEWEB)

    Gonzalez Florez, Ana Isabel

    2016-07-01

    The function of a biological molecule is closely related to its structure. As a result, understanding and predicting biomolecular structure has become the focus of an extensive field of research. However, the investigation of molecular structure can be hampered by two main difficulties: the inherent complications that may arise from studying biological molecules in their native environment, and the potential congestion of the experimental results as a consequence of the large number of degrees of freedom present in these molecules. In this work, a new experimental setup has been developed and established in order to overcome the afore mentioned limitations combining structure-sensitive gas-phase methods with superfluid helium droplets. First, biological molecules are ionised and brought into the gas phase, often referred to as a clean-room environment, where the species of interest are isolated from their surroundings and, thus, intermolecular interactions are absent. The mass-to-charge selected biomolecules are then embedded inside clusters of superfluid helium with an equilibrium temperature of ∝0.37 K. As a result, the internal energy of the molecules is lowered, thereby reducing the number of populated quantum states. Finally, the local hydrogen bonding patterns of the molecules are investigated by probing specific vibrational modes using the Fritz Haber Institute's free electron laser as a source of infrared radiation. Although the structure of a wide variety of molecules has been studied making use of the sub-Kelvin environment provided by superfluid helium droplets, the suitability of this method for the investigation of biological molecular ions was still unclear. However, the experimental results presented in this thesis demonstrate the applicability of this experimental approach in order to study the structure of intact, large biomolecular ions and the first vibrational spectrum of the protonated pentapeptide leu-enkephalin embedded in helium

  17. Multiple access protocol for supporting multimedia services in wireless ATM networks

    DEFF Research Database (Denmark)

    Liu, Hong; Dittmann, Lars; Gliese, Ulrik Bo

    1999-01-01

    The furture broadband wireless asynchronous transfer mode (ATM) networks must provide seamless extension of multimedia services from the wireline ATM networks. This requires an effecient wireless access protocol to fulfill varying Quality-og-Service (QoS) requirements for multimedia applications....... In this paper, we propose a multiple access protocol using centralized and distributed channel access control techniques to provide QoS guarantees for multimedia services by taking advantage of the characteristics of different kinds of ATM traffics. Multimedia traffic, including constant bit rate (CBR...

  18. Traffic Management by Using Admission Control Methods in Multiple Node IMS Network

    Directory of Open Access Journals (Sweden)

    Filip Chamraz

    2016-01-01

    Full Text Available The paper deals with Admission Control methods (AC as a possible solution for traffic management in IMS networks (IP Multimedia Subsystem - from the point of view of an efficient redistribution of the available network resources and keeping the parameters of Quality of Service (QoS. The paper specifically aims at the selection of the most appropriate method for the specific type of traffic and traffic management concept using AC methods on multiple nodes. The potential benefit and disadvantage of the used solution is evaluated.

  19. Stability and attractive basins of multiple equilibria in delayed two-neuron networks

    International Nuclear Information System (INIS)

    Huang Yu-Jiao; Zhang Hua-Guang; Wang Zhan-Shan

    2012-01-01

    Multiple stability for two-dimensional delayed recurrent neural networks with piecewise linear activation functions of 2r (r ≥ 1) corner points is studied. Sufficient conditions are established for checking the existence of (2r + 1) 2 equilibria in delayed recurrent neural networks. Under these conditions, (r + 1) 2 equilibria are locally exponentially stable, and (2r + 1) 2 — (r + 1) 2 — r 2 equilibria are unstable. Attractive basins of stable equilibria are estimated, which are larger than invariant sets derived by decomposing state space. One example is provided to illustrate the effectiveness of our results. (general)

  20. New results for global robust stability of bidirectional associative memory neural networks with multiple time delays

    International Nuclear Information System (INIS)

    Senan, Sibel; Arik, Sabri

    2009-01-01

    This paper presents some new sufficient conditions for the global robust asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with multiple time delays. The results we obtain impose constraint conditions on the network parameters of neural system independently of the delay parameter, and they are applicable to all bounded continuous non-monotonic neuron activation functions. We also give some numerical examples to demonstrate the applicability and effectiveness of our results, and compare the results with the previous robust stability results derived in the literature.

  1. Multiple-point statistical prediction on fracture networks at Yucca Mountain

    International Nuclear Information System (INIS)

    Liu, X.Y; Zhang, C.Y.; Liu, Q.S.; Birkholzer, J.T.

    2009-01-01

    In many underground nuclear waste repository systems, such as at Yucca Mountain, water flow rate and amount of water seepage into the waste emplacement drifts are mainly determined by hydrological properties of fracture network in the surrounding rock mass. Natural fracture network system is not easy to describe, especially with respect to its connectivity which is critically important for simulating the water flow field. In this paper, we introduced a new method for fracture network description and prediction, termed multi-point-statistics (MPS). The process of the MPS method is to record multiple-point statistics concerning the connectivity patterns of a fracture network from a known fracture map, and to reproduce multiple-scale training fracture patterns in a stochastic manner, implicitly and directly. It is applied to fracture data to study flow field behavior at the Yucca Mountain waste repository system. First, the MPS method is used to create a fracture network with an original fracture training image from Yucca Mountain dataset. After we adopt a harmonic and arithmetic average method to upscale the permeability to a coarse grid, THM simulation is carried out to study near-field water flow in the surrounding waste emplacement drifts. Our study shows that connectivity or patterns of fracture networks can be grasped and reconstructed by MPS methods. In theory, it will lead to better prediction of fracture system characteristics and flow behavior. Meanwhile, we can obtain variance from flow field, which gives us a way to quantify model uncertainty even in complicated coupled THM simulations. It indicates that MPS can potentially characterize and reconstruct natural fracture networks in a fractured rock mass with advantages of quantifying connectivity of fracture system and its simulation uncertainty simultaneously.

  2. NIMEFI: gene regulatory network inference using multiple ensemble feature importance algorithms.

    Directory of Open Access Journals (Sweden)

    Joeri Ruyssinck

    Full Text Available One of the long-standing open challenges in computational systems biology is the topology inference of gene regulatory networks from high-throughput omics data. Recently, two community-wide efforts, DREAM4 and DREAM5, have been established to benchmark network inference techniques using gene expression measurements. In these challenges the overall top performer was the GENIE3 algorithm. This method decomposes the network inference task into separate regression problems for each gene in the network in which the expression values of a particular target gene are predicted using all other genes as possible predictors. Next, using tree-based ensemble methods, an importance measure for each predictor gene is calculated with respect to the target gene and a high feature importance is considered as putative evidence of a regulatory link existing between both genes. The contribution of this work is twofold. First, we generalize the regression decomposition strategy of GENIE3 to other feature importance methods. We compare the performance of support vector regression, the elastic net, random forest regression, symbolic regression and their ensemble variants in this setting to the original GENIE3 algorithm. To create the ensemble variants, we propose a subsampling approach which allows us to cast any feature selection algorithm that produces a feature ranking into an ensemble feature importance algorithm. We demonstrate that the ensemble setting is key to the network inference task, as only ensemble variants achieve top performance. As second contribution, we explore the effect of using rankwise averaged predictions of multiple ensemble algorithms as opposed to only one. We name this approach NIMEFI (Network Inference using Multiple Ensemble Feature Importance algorithms and show that this approach outperforms all individual methods in general, although on a specific network a single method can perform better. An implementation of NIMEFI has been made

  3. Constraints on signaling network logic reveal functional subgraphs on Multiple Myeloma OMIC data.

    Science.gov (United States)

    Miannay, Bertrand; Minvielle, Stéphane; Magrangeas, Florence; Guziolowski, Carito

    2018-03-21

    The integration of gene expression profiles (GEPs) and large-scale biological networks derived from pathways databases is a subject which is being widely explored. Existing methods are based on network distance measures among significantly measured species. Only a small number of them include the directionality and underlying logic existing in biological networks. In this study we approach the GEP-networks integration problem by considering the network logic, however our approach does not require a prior species selection according to their gene expression level. We start by modeling the biological network representing its underlying logic using Logic Programming. This model points to reachable network discrete states that maximize a notion of harmony between the molecular species active or inactive possible states and the directionality of the pathways reactions according to their activator or inhibitor control role. Only then, we confront these network states with the GEP. From this confrontation independent graph components are derived, each of them related to a fixed and optimal assignment of active or inactive states. These components allow us to decompose a large-scale network into subgraphs and their molecular species state assignments have different degrees of similarity when compared to the same GEP. We apply our method to study the set of possible states derived from a subgraph from the NCI-PID Pathway Interaction Database. This graph links Multiple Myeloma (MM) genes to known receptors for this blood cancer. We discover that the NCI-PID MM graph had 15 independent components, and when confronted to 611 MM GEPs, we find 1 component as being more specific to represent the difference between cancer and healthy profiles.

  4. Priority and Negotiation Based Dynamic Spectrum Allocation Scheme for Multiple Radio Access Network Operators

    Science.gov (United States)

    Kim, Hoon; Hyon, Taein; Lee, Yeonwoo

    Most of previous works have presented the dynamic spectrum allocation (DSA) gain achieved by utilizing the time or regional variations in traffic demand between multi-network operators (NOs). In this paper, we introduce the functionalities required for the entities related with the spectrum sharing and allocation and propose a spectrum allocation algorithm while considering the long-term priority between NOs, the priority between multiple class services, and the urgent bandwidth request. To take into account the priorities among the NOs and the priorities of multiple class services, a spectrum sharing metric (SSM) is proposed, while a negotiation procedure is proposed to treat the urgent bandwidth request.

  5. A feedback control model for network flow with multiple pure time delays

    Science.gov (United States)

    Press, J.

    1972-01-01

    A control model describing a network flow hindered by multiple pure time (or transport) delays is formulated. Feedbacks connect each desired output with a single control sector situated at the origin. The dynamic formulation invokes the use of differential difference equations. This causes the characteristic equation of the model to consist of transcendental functions instead of a common algebraic polynomial. A general graphical criterion is developed to evaluate the stability of such a problem. A digital computer simulation confirms the validity of such criterion. An optimal decision making process with multiple delays is presented.

  6. Enforcement of Privacy Policies over Multiple Online Social Networks for Collaborative Activities

    Science.gov (United States)

    Wu, Zhengping; Wang, Lifeng

    Our goal is to tend to develop an enforcement architecture of privacy policies over multiple online social networks. It is used to solve the problem of privacy protection when several social networks build permanent or temporary collaboration. Theoretically, this idea is practical, especially due to more and more social network tend to support open source framework “OpenSocial”. But as we known different social network websites may have the same privacy policy settings based on different enforcement mechanisms, this would cause problems. In this case, we have to manually write code for both sides to make the privacy policy settings enforceable. We can imagine that, this is a huge workload based on the huge number of current social networks. So we focus on proposing a middleware which is used to automatically generate privacy protection component for permanent integration or temporary interaction of social networks. This middleware provide functions, such as collecting of privacy policy of each participant in the new collaboration, generating a standard policy model for each participant and mapping all those standard policy to different enforcement mechanisms of those participants.

  7. A study on the multiple dynamic wavelength distribution for gigabit capable passive optical networks

    Directory of Open Access Journals (Sweden)

    Gustavo Adolfo Puerto Leguizamón

    2014-04-01

    Full Text Available This paper presents a data traffic based study aiming at evaluating the impact of dynamic wavelength allocation on a Gigabit capable Passive Optical Network (GPON. In Passive Optical Networks (PON, an Optical Line Terminal (OLT feeds different PONs in such a way that a given wavelength channel is evenly distributed between the Optical Network Units (ONU at each PON. However, PONs do not specify any kind of dynamic behavior on the way the wavelengths are allocated in the network, a completely static distribution is implemented instead. In thispaper we evaluate the network performance in terms of packet losses and throughput for a number of ONUs being out-of-profile while featuring a given percentage of traffic in excess for a fixed wavelength distribution and for multiple dynamic wavelength allocation. Results show that for a multichannel operation with four wavelengths, the network throughput increases up to a rough value of 19% while the packet losses drop from 22 % to 1.8 % as compared with a static wavelength distribution.

  8. Efficient traffic grooming with dynamic ONU grouping for multiple-OLT-based access network

    Science.gov (United States)

    Zhang, Shizong; Gu, Rentao; Ji, Yuefeng; Wang, Hongxiang

    2015-12-01

    Fast bandwidth growth urges large-scale high-density access scenarios, where the multiple Passive Optical Networking (PON) system clustered deployment can be adopted as an appropriate solution to fulfill the huge bandwidth demands, especially for a future 5G mobile network. However, the lack of interaction between different optical line terminals (OLTs) results in part of the bandwidth resources waste. To increase the bandwidth efficiency, as well as reduce bandwidth pressure at the edge of a network, we propose a centralized flexible PON architecture based on Time- and Wavelength-Division Multiplexing PON (TWDM PON). It can provide flexible affiliation for optical network units (ONUs) and different OLTs to support access network traffic localization. Specifically, a dynamic ONU grouping algorithm (DGA) is provided to obtain the minimal OLT outbound traffic. Simulation results show that DGA obtains an average 25.23% traffic gain increment under different OLT numbers within a small ONU number situation, and the traffic gain will increase dramatically with the increment of the ONU number. As the DGA can be deployed easily as an application running above the centralized control plane, the proposed architecture can be helpful to improve the network efficiency for future traffic-intensive access scenarios.

  9. LAI inversion from optical reflectance using a neural network trained with a multiple scattering model

    Science.gov (United States)

    Smith, James A.

    1992-01-01

    The inversion of the leaf area index (LAI) canopy parameter from optical spectral reflectance measurements is obtained using a backpropagation artificial neural network trained using input-output pairs generated by a multiple scattering reflectance model. The problem of LAI estimation over sparse canopies (LAI 1000 percent for low LAI. Minimization methods applied to merit functions constructed from differences between measured reflectances and predicted reflectances using multiple-scattering models are unacceptably sensitive to a good initial guess for the desired parameter. In contrast, the neural network reported generally yields absolute percentage errors of <30 percent when weighting coefficients trained on one soil type were applied to predicted canopy reflectance at a different soil background.

  10. Synthetic tetracycline-inducible regulatory networks: computer-aided design of dynamic phenotypes

    Directory of Open Access Journals (Sweden)

    Kaznessis Yiannis N

    2007-01-01

    Full Text Available Abstract Background Tightly regulated gene networks, precisely controlling the expression of protein molecules, have received considerable interest by the biomedical community due to their promising applications. Among the most well studied inducible transcription systems are the tetracycline regulatory expression systems based on the tetracycline resistance operon of Escherichia coli, Tet-Off (tTA and Tet-On (rtTA. Despite their initial success and improved designs, limitations still persist, such as low inducer sensitivity. Instead of looking at these networks statically, and simply changing or mutating the promoter and operator regions with trial and error, a systematic investigation of the dynamic behavior of the network can result in rational design of regulatory gene expression systems. Sophisticated algorithms can accurately capture the dynamical behavior of gene networks. With computer aided design, we aim to improve the synthesis of regulatory networks and propose new designs that enable tighter control of expression. Results In this paper we engineer novel networks by recombining existing genes or part of genes. We synthesize four novel regulatory networks based on the Tet-Off and Tet-On systems. We model all the known individual biomolecular interactions involved in transcription, translation, regulation and induction. With multiple time-scale stochastic-discrete and stochastic-continuous models we accurately capture the transient and steady state dynamics of these networks. Important biomolecular interactions are identified and the strength of the interactions engineered to satisfy design criteria. A set of clear design rules is developed and appropriate mutants of regulatory proteins and operator sites are proposed. Conclusion The complexity of biomolecular interactions is accurately captured through computer simulations. Computer simulations allow us to look into the molecular level, portray the dynamic behavior of gene regulatory

  11. Multiple Regions of a Cortical Network Commonly Encode the Meaning of Words in Multiple Grammatical Positions of Read Sentences.

    Science.gov (United States)

    Anderson, Andrew James; Lalor, Edmund C; Lin, Feng; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Raizada, Rajeev D S; Grimm, Scott; Wang, Xixi

    2018-05-16

    Deciphering how sentence meaning is represented in the brain remains a major challenge to science. Semantically related neural activity has recently been shown to arise concurrently in distributed brain regions as successive words in a sentence are read. However, what semantic content is represented by different regions, what is common across them, and how this relates to words in different grammatical positions of sentences is weakly understood. To address these questions, we apply a semantic model of word meaning to interpret brain activation patterns elicited in sentence reading. The model is based on human ratings of 65 sensory/motor/emotional and cognitive features of experience with words (and their referents). Through a process of mapping functional Magnetic Resonance Imaging activation back into model space we test: which brain regions semantically encode content words in different grammatical positions (e.g., subject/verb/object); and what semantic features are encoded by different regions. In left temporal, inferior parietal, and inferior/superior frontal regions we detect the semantic encoding of words in all grammatical positions tested and reveal multiple common components of semantic representation. This suggests that sentence comprehension involves a common core representation of multiple words' meaning being encoded in a network of regions distributed across the brain.

  12. Allocation and management issues in multiple-transaction open access transmission networks

    Science.gov (United States)

    Tao, Shu

    This thesis focuses on some key issues related to allocation and management by the independent grid operator (IGO) of unbundled services in multiple-transaction open access transmission networks. The three unbundled services addressed in the thesis are transmission real power losses, reactive power support requirements from generation sources, and transmission congestion management. We develop the general framework that explicitly represents multiple transactions undertaken simultaneously in the transmission grid. This framework serves as the basis for formulating various problems treated in the thesis. We use this comprehensive framework to develop a physical-flow-based mechanism to allocate the total transmission losses to each transaction using the system. An important property of the allocation scheme is its capability to effectively deal with counter flows that result in the presence of specific transactions. Using the loss allocation results as the basis, we construct the equivalent loss compensation concept and apply it to develop flexible and effective procedures for compensating losses in multiple-transaction networks. We present a new physical-flow-based mechanism for allocating the reactive power support requirements provided by generators in multiple-transaction networks. The allocatable reactive support requirements are formulated as the sum of two specific components---the voltage magnitude variation component and the voltage angle variation component. The formulation utilizes the multiple-transaction framework and makes use of certain simplifying approximations. The formulation leads to a natural allocation as a function of the amount of each transaction. The physical interpretation of each allocation as a sensitivity of the reactive output of a generator is discussed. We propose a congestion management allocation scheme for multiple-transaction networks. The proposed scheme determines the allocation of congestion among the transactions on a physical

  13. Smart Control of Multiple Evaporator Systems with Wireless Sensor and Actuator Networks

    Directory of Open Access Journals (Sweden)

    Apolinar González-Potes

    2016-02-01

    Full Text Available This paper describes the complete integration of a fuzzy control of multiple evaporator systems with the IEEE 802.15.4 standard, in which we study several important aspects for this kind of system, like a detailed analysis of the end-to-end real-time flows over wireless sensor and actuator networks (WSAN, a real-time kernel with an earliest deadline first (EDF scheduler, periodic and aperiodic tasking models for the nodes, lightweight and flexible compensation-based control algorithms for WSAN that exhibit packet dropouts, an event-triggered sampling scheme and design methodologies. We address the control problem of the multi-evaporators with the presence of uncertainties, which was tackled through a wireless fuzzy control approach, showing the advantages of this concept where it can easily perform the optimization for a set of multiple evaporators controlled by the same smart controller, which should have an intelligent and flexible architecture based on multi-agent systems (MAS that allows one to add or remove new evaporators online, without the need for reconfiguring, while maintaining temporal and functional restrictions in the system. We show clearly how we can get a greater scalability, the self-configuration of the network and the least overhead with a non-beacon or unslotted mode of the IEEE 802.15.4 protocol, as well as wireless communications and distributed architectures, which could be extremely helpful in the development process of networked control systems in large spatially-distributed plants, which involve many sensors and actuators. For this purpose, a fuzzy scheme is used to control a set of parallel evaporator air-conditioning systems, with temperature and relative humidity control as a multi-input and multi-output closed loop system; in addition, a general architecture is presented, which implements multiple control loops closed over a communication network, integrating the analysis and validation method for multi

  14. Optimal power allocation of a single transmitter-multiple receivers channel in a cognitive sensor network

    KAUST Repository

    Ayala Solares, Jose Roberto

    2012-08-01

    The optimal transmit power of a wireless sensor network with one transmitter and multiple receivers in a cognitive radio environment while satisfying independent peak, independent average, sum of peak and sum of average transmission rate constraints is derived. A suboptimal scheme is proposed to overcome the frequency of outages for the independent peak transmission rate constraint. In all cases, numerical results are provided for Rayleigh fading channels. © 2012 IEEE.

  15. Energy-Aware Routing in Multiple Domains Software-Defined Networks

    Directory of Open Access Journals (Sweden)

    Adriana FERNÁNDEZ-FERNÁNDEZ

    2016-12-01

    Full Text Available The growing energy consumption of communication networks has attracted the attention of the networking researchers in the last decade. In this context, the new architecture of Software-Defined Networks (SDN allows a flexible programmability, suitable for the power-consumption optimization problem. In this paper we address the issue of designing a novel distributed routing algorithm that optimizes the power consumption in large scale SDN with multiple domains. The solution proposed, called DEAR (Distributed Energy-Aware Routing, tackles the problem of minimizing the number of links that can be used to satisfy a given data traffic demand under performance constraints such as control traffic delay and link utilization. To this end, we present a complete formulation of the optimization problem that considers routing requirements for control and data plane communications. Simulation results confirm that the proposed solution enables the achievement of significant energy savings.

  16. Rock property estimates using multiple seismic attributes and neural networks; Pegasus Field, West Texas

    Energy Technology Data Exchange (ETDEWEB)

    Schuelke, J.S.; Quirein, J.A.; Sarg, J.F.

    1998-12-31

    This case study shows the benefit of using multiple seismic trace attributes and the pattern recognition capabilities of neural networks to predict reservoir architecture and porosity distribution in the Pegasus Field, West Texas. The study used the power of neural networks to integrate geologic, borehole and seismic data. Illustrated are the improvements between the new neural network approach and the more traditional method of seismic trace inversion for porosity estimation. Comprehensive statistical methods and interpretational/subjective measures are used in the prediction of porosity from seismic attributes. A 3-D volume of seismic derived porosity estimates for the Devonian reservoir provide a very detailed estimate of porosity, both spatially and vertically, for the field. The additional reservoir porosity detail provided, between the well control, allows for optimal placement of horizontal wells and improved field development. 6 refs., 2 figs.

  17. Maximizing the Lifetime of Wireless Sensor Networks Using Multiple Sets of Rendezvous

    Directory of Open Access Journals (Sweden)

    Bo Li

    2015-01-01

    Full Text Available In wireless sensor networks (WSNs, there is a “crowded center effect” where the energy of nodes located near a data sink drains much faster than other nodes resulting in a short network lifetime. To mitigate the “crowded center effect,” rendezvous points (RPs are used to gather data from other nodes. In order to prolong the lifetime of WSN further, we propose using multiple sets of RPs in turn to average the energy consumption of the RPs. The problem is how to select the multiple sets of RPs and how long to use each set of RPs. An optimal algorithm and a heuristic algorithm are proposed to address this problem. The optimal algorithm is highly complex and only suitable for small scale WSN. The performance of the proposed algorithms is evaluated through simulations. The simulation results indicate that the heuristic algorithm approaches the optimal one and that using multiple RP sets can significantly prolong network lifetime.

  18. Implementation of Multiple Host Nodes in Wireless Sensing Node Network System for Landslide Monitoring

    International Nuclear Information System (INIS)

    Bin Abas, Faizulsalihin; Takayama, Shigeru

    2015-01-01

    This paper proposes multiple host nodes in Wireless Sensing Node Network System (WSNNS) for landslide monitoring. As landslide disasters damage monitoring system easily, one major demand in landslide monitoring is the flexibility and robustness of the system to evaluate the current situation in the monitored area. For various reasons WSNNS can provide an important contribution to reach that aim. In this system, acceleration sensors and GPS are deployed in sensing nodes. Location information by GPS, enable the system to estimate network topology and enable the system to perceive the location in emergency by monitoring the node mode. Acceleration sensors deployment, capacitate this system to detect slow mass movement that can lead to landslide occurrence. Once deployed, sensing nodes self-organize into an autonomous wireless ad hoc network. The measurement parameter data from sensing nodes is transmitted to Host System via host node and ''Cloud'' System. The implementation of multiple host nodes in Local Sensing Node Network System (LSNNS), improve risk- management of the WSNNS for real-time monitoring of landslide disaster

  19. Parity-Check Network Coding for Multiple Access Relay Channel in Wireless Sensor Cooperative Communications

    Directory of Open Access Journals (Sweden)

    Du Bing

    2010-01-01

    Full Text Available A recently developed theory suggests that network coding is a generalization of source coding and channel coding and thus yields a significant performance improvement in terms of throughput and spatial diversity. This paper proposes a cooperative design of a parity-check network coding scheme in the context of a two-source multiple access relay channel (MARC model, a common compact model in hierarchical wireless sensor networks (WSNs. The scheme uses Low-Density Parity-Check (LDPC as the surrogate to build up a layered structure which encapsulates the multiple constituent LDPC codes in the source and relay nodes. Specifically, the relay node decodes the messages from two sources, which are used to generate extra parity-check bits by a random network coding procedure to fill up the rate gap between Source-Relay and Source-Destination transmissions. Then, we derived the key algebraic relationships among multidimensional LDPC constituent codes as one of the constraints for code profile optimization. These extra check bits are sent to the destination to realize a cooperative diversity as well as to approach MARC decode-and-forward (DF capacity.

  20. A System for Acquisition, Processing and Visualization of Image Time Series from Multiple Camera Networks

    Directory of Open Access Journals (Sweden)

    Cemal Melih Tanis

    2018-06-01

    Full Text Available A system for multiple camera networks is proposed for continuous monitoring of ecosystems by processing image time series. The system is built around the Finnish Meteorological Image PROcessing Toolbox (FMIPROT, which includes data acquisition, processing and visualization from multiple camera networks. The toolbox has a user-friendly graphical user interface (GUI for which only minimal computer knowledge and skills are required to use it. Images from camera networks are acquired and handled automatically according to the common communication protocols, e.g., File Transfer Protocol (FTP. Processing features include GUI based selection of the region of interest (ROI, automatic analysis chain, extraction of ROI based indices such as the green fraction index (GF, red fraction index (RF, blue fraction index (BF, green-red vegetation index (GRVI, and green excess (GEI index, as well as a custom index defined by a user-provided mathematical formula. Analysis results are visualized on interactive plots both on the GUI and hypertext markup language (HTML reports. The users can implement their own developed algorithms to extract information from digital image series for any purpose. The toolbox can also be run in non-GUI mode, which allows running series of analyses in servers unattended and scheduled. The system is demonstrated using an environmental camera network in Finland.

  1. Implementation of Multiple Host Nodes in Wireless Sensing Node Network System for Landslide Monitoring

    Science.gov (United States)

    Abas, Faizulsalihin bin; Takayama, Shigeru

    2015-02-01

    This paper proposes multiple host nodes in Wireless Sensing Node Network System (WSNNS) for landslide monitoring. As landslide disasters damage monitoring system easily, one major demand in landslide monitoring is the flexibility and robustness of the system to evaluate the current situation in the monitored area. For various reasons WSNNS can provide an important contribution to reach that aim. In this system, acceleration sensors and GPS are deployed in sensing nodes. Location information by GPS, enable the system to estimate network topology and enable the system to perceive the location in emergency by monitoring the node mode. Acceleration sensors deployment, capacitate this system to detect slow mass movement that can lead to landslide occurrence. Once deployed, sensing nodes self-organize into an autonomous wireless ad hoc network. The measurement parameter data from sensing nodes is transmitted to Host System via host node and "Cloud" System. The implementation of multiple host nodes in Local Sensing Node Network System (LSNNS), improve risk- management of the WSNNS for real-time monitoring of landslide disaster.

  2. Performance analysis of an opportunistic multi-user cognitive network with multiple primary users

    KAUST Repository

    Khan, Fahd Ahmed

    2014-03-01

    Consider a multi-user underlay cognitive network where multiple cognitive users concurrently share the spectrum with a primary network with multiple users. The channel between the secondary network is assumed to have independent but not identical Nakagami-m fading. The interference channel between the secondary users (SUs) and the primary users is assumed to have Rayleigh fading. A power allocation based on the instantaneous channel state information is derived when a peak interference power constraint is imposed on the secondary network in addition to the limited peak transmit power of each SU. The uplink scenario is considered where a single SU is selected for transmission. This opportunistic selection depends on the transmission channel power gain and the interference channel power gain as well as the power allocation policy adopted at the users. Exact closed form expressions for the moment-generating function, outage performance, symbol error rate performance, and the ergodic capacity are derived. Numerical results corroborate the derived analytical results. The performance is also studied in the asymptotic regimes, and the generalized diversity gain of this scheduling scheme is derived. It is shown that when the interference channel is deeply faded and the peak transmit power constraint is relaxed, the scheduling scheme achieves full diversity and that increasing the number of primary users does not impact the diversity order. © 2014 John Wiley & Sons, Ltd.

  3. Laser photodissociation and spectroscopy of mass-separated biomolecular ions

    CERN Document Server

    Polfer, Nicolas C

    2014-01-01

    This lecture notes book presents how enhanced structural information of biomolecular ions can be obtained from interaction with photons of specific frequency - laser light. The methods described in the book ""Laser photodissociation and spectroscopy of mass-separated biomolecular ions"" make use of the fact that the discrete energy and fast time scale of photoexcitation can provide more control in ion activation. This activation is the crucial process producing structure-informative product ions that cannot be generated with more conventional heating methods, such as collisional activation. Th

  4. Image transmission in multicore-fiber code-division multiple access network

    Science.gov (United States)

    Yang, Guu-Chang; Kwong, Wing C.

    1997-01-01

    Recently, two-dimensional (2-D) signature patterns were proposed to encode binary digitized image pixels in optical code-division multiple-access (CDMA) networks with 'multicore' fiber. The new technology enables parallel transmission and simultaneous access of 2-D images in multiple-access environment, where these signature patterns are defined as optical orthogonal signature pattern codes (OOSPCs). However, previous work on OOSPCs assumed that the weight of each signature pattern was the same. In this paper, we construct a new family of OOSPCs with the removal of this assumption. Since varying the weight of a user's signature pattern affects that user's performance, this approach is useful for CDMA optical systems with multiple performance requirements.

  5. Information processing speed and attention in multiple sclerosis: Reconsidering the Attention Network Test (ANT).

    Science.gov (United States)

    Roth, Alexandra K; Denney, Douglas R; Lynch, Sharon G

    2015-01-01

    The Attention Network Test (ANT) assesses attention in terms of discrepancies between response times to items that differ in the burden they place on some facet of attention. However, simple arithmetic difference scores commonly used to capture these discrepancies fail to provide adequate control for information processing speed, leading to distorted findings when patient and control groups differ markedly in the speed with which they process and respond to stimulus information. This study examined attention networks in patients with multiple sclerosis (MS) using simple difference scores, proportional scores, and residualized scores that control for processing speed through statistical regression. Patients with relapsing-remitting (N = 20) or secondary progressive (N = 20) MS and healthy controls (N = 40) of similar age, education, and gender completed the ANT. Substantial differences between patients and controls were found on all measures of processing speed. Patients exhibited difficulties in the executive control network, but only when difference scores were considered. When deficits in information processing speed were adequately controlled using proportional or residualized score, deficits in the alerting network emerged. The effect sizes for these deficits were notably smaller than those for overall information processing speed and were also limited to patients with secondary progressive MS. Deficits in processing speed are more prominent in MS than those involving attention, and when the former are properly accounted for, differences in the latter are confined to the alerting network.

  6. Multiple effect of social influence on cooperation in interdependent network games

    Science.gov (United States)

    Jiang, Luo-Luo; Li, Wen-Jing; Wang, Zhen

    2015-10-01

    The social influence exists widely in the human society, where individual decision-making process (from congressional election to electronic commerce) may be affected by the attitude and behavior of others belonging to different social networks. Here, we couple the snowdrift (SD) game and the prisoner’s dilemma (PD) game on two interdependent networks, where strategies in both games are associated by social influence to mimick the majority rule. More accurately, individuals’ strategies updating refers to social learning (based on payoff difference) and above-mentioned social influence (related with environment of interdependent group), which is controlled by social influence strength s. Setting s = 0 decouples the networks and returns the traditional network game; while its increase involves the interactions between networks. By means of numerous Monte Carlo simulations, we find that such a mechanism brings multiple influence to the evolution of cooperation. Small s leads to unequal cooperation level in both games, because social learning is still the main updating rule for most players. Though intermediate and large s guarantees the synchronized evolution of strategy pairs, cooperation finally dies out and reaches a completely dominance in both cases. Interestingly, these observations are attributed to the expansion of cooperation clusters. Our work may provide a new understanding to the emergence of cooperation in intercorrelated social systems.

  7. An Adaptive Time-Spread Multiple-Access Policy for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Konstantinos Oikonomou

    2007-05-01

    Full Text Available Sensor networks require a simple and efficient medium access control policy achieving high system throughput with no or limited control overhead in order to increase the network lifetime by minimizing the energy consumed during transmission attempts. Time-spread multiple-access (TSMA policies that have been proposed for ad hoc network environments, can also be employed in sensor networks, since no control overhead is introduced. However, they do not take advantage of any cross-layer information in order to exploit the idiosyncrasies of the particular sensor network environment such as the presence of typically static nodes and a common destination for the forwarded data. An adaptive probabilistic TSMA-based policy, that is proposed and analyzed in this paper, exploits these idiosyncrasies and achieves higher system throughput than the existing TSMA-based policies without any need for extra control overhead. As it is analytically shown in this paper, the proposed policy always outperforms the existing TSMA-based policies, if certain parameter values are properly set; the analysis also provides for these proper values. It is also shown that the proposed policy is characterized by a certain convergence period and that high system throughput is achieved for long convergence periods. The claims and expectations of the provided analysis are supported by simulation results presented in this paper.

  8. Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks.

    Science.gov (United States)

    Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S

    2017-08-03

    Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a = ( u , v ) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages.

  9. Structural networks involved in attention and executive functions in multiple sclerosis

    Directory of Open Access Journals (Sweden)

    Sara Llufriu

    2017-01-01

    Full Text Available Attention and executive deficits are disabling symptoms in multiple sclerosis (MS that have been related to disconnection mechanisms. We aimed to investigate changes in structural connectivity in MS and their association with attention and executive performance applying an improved framework that combines high order probabilistic tractography and anatomical exclusion criteria postprocessing. We compared graph theory metrics of structural networks and fractional anisotropy (FA of white matter (WM connections or edges between 72 MS subjects and 38 healthy volunteers (HV and assessed their correlation with cognition. Patients displayed decreased network transitivity, global efficiency and increased path length compared with HV (p < 0.05, corrected. Also, nodal strength was decreased in 26 of 84 gray matter regions. The distribution of nodes with stronger connections or hubs of the network was similar among groups except for the right pallidum and left insula, which became hubs in patients. MS subjects presented reduced edge FA widespread in the network, while FA was increased in 24 connections (p < 0.05, corrected. Decreased integrity of frontoparietal networks, deep gray nuclei and insula correlated with worse attention and executive performance (r between 0.38 and 0.55, p < 0.05, corrected. Contrarily, higher strength in the right transverse temporal cortex and increased FA of several connections (mainly from cingulate, frontal and occipital cortices were associated with worse functioning (r between −0.40 and −0.47, p < 0.05 corrected. In conclusion, structural brain connectivity is disturbed in MS due to widespread impairment of WM connections and gray matter structures. The increased edge connectivity suggests the presence of reorganization mechanisms at the structural level. Importantly, attention and executive performance relates to frontoparietal networks, deep gray nuclei and insula. These results support the relevance of

  10. Engineering intracellular active transport systems as in vivo biomolecular tools.

    Energy Technology Data Exchange (ETDEWEB)

    Bachand, George David; Carroll-Portillo, Amanda

    2006-11-01

    Active transport systems provide essential functions in terms of cell physiology and metastasis. These systems, however, are also co-opted by invading viruses, enabling directed transport of the virus to and from the cell's nucleus (i.e., the site of virus replication). Based on this concept, fundamentally new approaches for interrogating and manipulating the inner workings of living cells may be achievable by co-opting Nature's active transport systems as an in vivo biomolecular tool. The overall goal of this project was to investigate the ability to engineer kinesin-based transport systems for in vivo applications, specifically the collection of effector proteins (e.g., transcriptional regulators) within single cells. In the first part of this project, a chimeric fusion protein consisting of kinesin and a single chain variable fragment (scFv) of an antibody was successfully produced through a recombinant expression system. The kinesin-scFv retained both catalytic and antigenic functionality, enabling selective capture and transport of target antigens. The incorporation of a rabbit IgG-specific scFv into the kinesin established a generalized system for functionalizing kinesin with a wide range of target-selective antibodies raised in rabbits. The second objective was to develop methods of isolating the intact microtubule network from live cells as a platform for evaluating kinesin-based transport within the cytoskeletal architecture of a cell. Successful isolation of intact microtubule networks from two distinct cell types was demonstrated using glutaraldehyde and methanol fixation methods. This work provides a platform for inferring the ability of kinesin-scFv to function in vivo, and may also serve as a three-dimensional scaffold for evaluating and exploiting kinesin-based transport for nanotechnological applications. Overall, the technology developed in this project represents a first-step in engineering active transport system for in vivo

  11. Spatial heterogeneity regulates plant-pollinator networks across multiple landscape scales.

    Directory of Open Access Journals (Sweden)

    Eduardo Freitas Moreira

    Full Text Available Mutualistic plant-pollinator interactions play a key role in biodiversity conservation and ecosystem functioning. In a community, the combination of these interactions can generate emergent properties, e.g., robustness and resilience to disturbances such as fluctuations in populations and extinctions. Given that these systems are hierarchical and complex, environmental changes must have multiple levels of influence. In addition, changes in habitat quality and in the landscape structure are important threats to plants, pollinators and their interactions. However, despite the importance of these phenomena for the understanding of biological systems, as well as for conservation and management strategies, few studies have empirically evaluated these effects at the network level. Therefore, the objective of this study was to investigate the influence of local conditions and landscape structure at multiple scales on the characteristics of plant-pollinator networks. This study was conducted in agri-natural lands in Chapada Diamantina, Bahia, Brazil. Pollinators were collected in 27 sampling units distributed orthogonally along a gradient of proportion of agriculture and landscape diversity. The Akaike information criterion was used to select models that best fit the metrics for network characteristics, comparing four hypotheses represented by a set of a priori candidate models with specific combinations of the proportion of agriculture, the average shape of the landscape elements, the diversity of the landscape and the structure of local vegetation. The results indicate that a reduction of habitat quality and landscape heterogeneity can cause species loss and decrease of networks nestedness. These structural changes can reduce robustness and resilience of plant-pollinator networks what compromises the reproductive success of plants, the maintenance of biodiversity and the pollination service stability. We also discuss the possible explanations for

  12. Spatial heterogeneity regulates plant-pollinator networks across multiple landscape scales.

    Science.gov (United States)

    Moreira, Eduardo Freitas; Boscolo, Danilo; Viana, Blandina Felipe

    2015-01-01

    Mutualistic plant-pollinator interactions play a key role in biodiversity conservation and ecosystem functioning. In a community, the combination of these interactions can generate emergent properties, e.g., robustness and resilience to disturbances such as fluctuations in populations and extinctions. Given that these systems are hierarchical and complex, environmental changes must have multiple levels of influence. In addition, changes in habitat quality and in the landscape structure are important threats to plants, pollinators and their interactions. However, despite the importance of these phenomena for the understanding of biological systems, as well as for conservation and management strategies, few studies have empirically evaluated these effects at the network level. Therefore, the objective of this study was to investigate the influence of local conditions and landscape structure at multiple scales on the characteristics of plant-pollinator networks. This study was conducted in agri-natural lands in Chapada Diamantina, Bahia, Brazil. Pollinators were collected in 27 sampling units distributed orthogonally along a gradient of proportion of agriculture and landscape diversity. The Akaike information criterion was used to select models that best fit the metrics for network characteristics, comparing four hypotheses represented by a set of a priori candidate models with specific combinations of the proportion of agriculture, the average shape of the landscape elements, the diversity of the landscape and the structure of local vegetation. The results indicate that a reduction of habitat quality and landscape heterogeneity can cause species loss and decrease of networks nestedness. These structural changes can reduce robustness and resilience of plant-pollinator networks what compromises the reproductive success of plants, the maintenance of biodiversity and the pollination service stability. We also discuss the possible explanations for these relationships and

  13. Insights Into the Bifunctional Aphidicolan-16-ß-ol Synthase Through Rapid Biomolecular Modeling Approaches.

    Science.gov (United States)

    Hirte, Max; Meese, Nicolas; Mertz, Michael; Fuchs, Monika; Brück, Thomas B

    2018-01-01

    Diterpene synthases catalyze complex, multi-step C-C coupling reactions thereby converting the universal, aliphatic precursor geranylgeranyl diphosphate into diverse olefinic macrocylces that form the basis for the structural diversity of the diterpene natural product family. Since catalytically relevant crystal structures of diterpene synthases are scarce, homology based biomolecular modeling techniques offer an alternative route to study the enzyme's reaction mechanism. However, precise identification of catalytically relevant amino acids is challenging since these models require careful preparation and refinement techniques prior to substrate docking studies. Targeted amino acid substitutions in this protein class can initiate premature quenching of the carbocation centered reaction cascade. The structural characterization of those alternative cyclization products allows for elucidation of the cyclization reaction cascade and provides a new source for complex macrocyclic synthons. In this study, new insights into structure and function of the fungal, bifunctional Aphidicolan-16-ß-ol synthase were achieved using a simplified biomolecular modeling strategy. The applied refinement methodologies could rapidly generate a reliable protein-ligand complex, which provides for an accurate in silico identification of catalytically relevant amino acids. Guided by our modeling data, ACS mutations lead to the identification of the catalytically relevant ACS amino acid network I626, T657, Y658, A786, F789, and Y923. Moreover, the ACS amino acid substitutions Y658L and D661A resulted in a premature termination of the cyclization reaction cascade en-route from syn-copalyl diphosphate to Aphidicolan-16-ß-ol. Both ACS mutants generated the diterpene macrocycle syn-copalol and a minor, non-hydroxylated labdane related diterpene, respectively. Our biomolecular modeling and mutational studies suggest that the ACS substrate cyclization occurs in a spatially restricted location of

  14. Insights Into the Bifunctional Aphidicolan-16-ß-ol Synthase Through Rapid Biomolecular Modeling Approaches

    Directory of Open Access Journals (Sweden)

    Max Hirte

    2018-04-01

    Full Text Available Diterpene synthases catalyze complex, multi-step C-C coupling reactions thereby converting the universal, aliphatic precursor geranylgeranyl diphosphate into diverse olefinic macrocylces that form the basis for the structural diversity of the diterpene natural product family. Since catalytically relevant crystal structures of diterpene synthases are scarce, homology based biomolecular modeling techniques offer an alternative route to study the enzyme's reaction mechanism. However, precise identification of catalytically relevant amino acids is challenging since these models require careful preparation and refinement techniques prior to substrate docking studies. Targeted amino acid substitutions in this protein class can initiate premature quenching of the carbocation centered reaction cascade. The structural characterization of those alternative cyclization products allows for elucidation of the cyclization reaction cascade and provides a new source for complex macrocyclic synthons. In this study, new insights into structure and function of the fungal, bifunctional Aphidicolan-16-ß-ol synthase were achieved using a simplified biomolecular modeling strategy. The applied refinement methodologies could rapidly generate a reliable protein-ligand complex, which provides for an accurate in silico identification of catalytically relevant amino acids. Guided by our modeling data, ACS mutations lead to the identification of the catalytically relevant ACS amino acid network I626, T657, Y658, A786, F789, and Y923. Moreover, the ACS amino acid substitutions Y658L and D661A resulted in a premature termination of the cyclization reaction cascade en-route from syn-copalyl diphosphate to Aphidicolan-16-ß-ol. Both ACS mutants generated the diterpene macrocycle syn-copalol and a minor, non-hydroxylated labdane related diterpene, respectively. Our biomolecular modeling and mutational studies suggest that the ACS substrate cyclization occurs in a spatially

  15. Insights into the bifunctional Aphidicolan-16-ß-ol synthase through rapid biomolecular modelling approaches

    Science.gov (United States)

    Hirte, Max; Meese, Nicolas; Mertz, Michael; Fuchs, Monika; Brück, Thomas B.

    2018-04-01

    Diterpene synthases catalyze complex, multi-step C-C coupling reactions thereby converting the universal, aliphatic precursor geranylgeranyl diphosphate into diverse olefinic macrocylces that form the basis for the structural diversity of the diterpene natural product family. Since catalytically relevant crystal structures of diterpene synthases are scarce, homology based biomolecular modelling techniques offer an alternative route to study the enzyme’s reaction mechanism. However, precise identification of catalytically relevant amino acids is challenging since these models require careful preparation and refinement techniques prior to substrate docking studies. Targeted amino acid substitutions in this protein class can initiate premature quenching of the carbocation centered reaction cascade. The structural characterization of those alternative cyclization products allows for elucidation of the cyclization reaction cascade and provides a new source for complex macrocyclic synthons. In this study, new insights into structure and function of the fungal, bifunctional Aphidicolan-16-ß-ol synthase were achieved using a simplified biomolecular modelling strategy. The applied refinement methodologies could rapidly generate a reliable protein-ligand complex, which provides for an accurate in silico identification of catalytically relevant amino acids. Guided by our modelling data, ACS mutations lead to the identification of the catalytically relevant ACS amino acid network I626, T657, Y658, A786, F789 and Y923. Moreover, the ACS amino acid substitutions Y658L and D661A resulted in a premature termination of the cyclization reaction cascade en-route from syn-copalyl diphosphate to Aphidicolan-16-ß-ol. Both ACS mutants generated the diterpene macrocycle syn-copalol and a minor, non-hydroxylated labdane related diterpene, respectively. Our biomolecular modelling and mutational studies suggest that the ACS substrate cyclization occurs in a spatially restricted location

  16. Systematic Analysis of the Multiple Bioactivities of Green Tea through a Network Pharmacology Approach

    Directory of Open Access Journals (Sweden)

    Shoude Zhang

    2014-01-01

    Full Text Available During the past decades, a number of studies have demonstrated multiple beneficial health effects of green tea. Polyphenolics are the most biologically active components of green tea. Many targets can be targeted or affected by polyphenolics. In this study, we excavated all of the targets of green tea polyphenolics (GTPs though literature mining and target calculation and analyzed the multiple pharmacology actions of green tea comprehensively through a network pharmacology approach. In the end, a total of 200 Homo sapiens targets were identified for fifteen GTPs. These targets were classified into six groups according to their related disease, which included cancer, diabetes, neurodegenerative disease, cardiovascular disease, muscular disease, and inflammation. Moreover, these targets mapped into 143 KEGG pathways, 26 of which were more enriched, as determined though pathway enrichment analysis and target-pathway network analysis. Among the identified pathways, 20 pathways were selected for analyzing the mechanisms of green tea in these diseases. Overall, this study systematically illustrated the mechanisms of the pleiotropic activity of green tea by analyzing the corresponding “drug-target-pathway-disease” interaction network.

  17. Joint multiple fully connected convolutional neural network with extreme learning machine for hepatocellular carcinoma nuclei grading.

    Science.gov (United States)

    Li, Siqi; Jiang, Huiyan; Pang, Wenbo

    2017-05-01

    Accurate cell grading of cancerous tissue pathological image is of great importance in medical diagnosis and treatment. This paper proposes a joint multiple fully connected convolutional neural network with extreme learning machine (MFC-CNN-ELM) architecture for hepatocellular carcinoma (HCC) nuclei grading. First, in preprocessing stage, each grayscale image patch with the fixed size is obtained using center-proliferation segmentation (CPS) method and the corresponding labels are marked under the guidance of three pathologists. Next, a multiple fully connected convolutional neural network (MFC-CNN) is designed to extract the multi-form feature vectors of each input image automatically, which considers multi-scale contextual information of deep layer maps sufficiently. After that, a convolutional neural network extreme learning machine (CNN-ELM) model is proposed to grade HCC nuclei. Finally, a back propagation (BP) algorithm, which contains a new up-sample method, is utilized to train MFC-CNN-ELM architecture. The experiment comparison results demonstrate that our proposed MFC-CNN-ELM has superior performance compared with related works for HCC nuclei grading. Meanwhile, external validation using ICPR 2014 HEp-2 cell dataset shows the good generalization of our MFC-CNN-ELM architecture. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. The heat-shock protein/chaperone network and multiple stress resistance.

    Science.gov (United States)

    Jacob, Pierre; Hirt, Heribert; Bendahmane, Abdelhafid

    2017-04-01

    Crop yield has been greatly enhanced during the last century. However, most elite cultivars are adapted to temperate climates and are not well suited to more stressful conditions. In the context of climate change, stress resistance is a major concern. To overcome these difficulties, scientists may help breeders by providing genetic markers associated with stress resistance. However, multistress resistance cannot be obtained from the simple addition of single stress resistance traits. In the field, stresses are unpredictable and several may occur at once. Consequently, the use of single stress resistance traits is often inadequate. Although it has been historically linked with the heat stress response, the heat-shock protein (HSP)/chaperone network is a major component of multiple stress responses. Among the HSP/chaperone 'client proteins', many are primary metabolism enzymes and signal transduction components with essential roles for the proper functioning of a cell. HSPs/chaperones are controlled by the action of diverse heat-shock factors, which are recruited under stress conditions. In this review, we give an overview of the regulation of the HSP/chaperone network with a focus on Arabidopsis thaliana. We illustrate the role of HSPs/chaperones in regulating diverse signalling pathways and discuss several basic principles that should be considered for engineering multiple stress resistance in crops through the HSP/chaperone network. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

  19. GROMOS++Software for the Analysis of Biomolecular Simulation Trajectories

    NARCIS (Netherlands)

    Eichenberger, A.P.; Allison, J.R.; Dolenc, J.; Geerke, D.P.; Horta, B.A.C.; Meier, K; Oostenbrink, B.C.; Schmid, N.; Steiner, D; Wang, D.; van Gunsteren, W.F.

    2011-01-01

    GROMOS++ is a set of C++ programs for pre- and postprocessing of molecular dynamics simulation trajectories and as such is part of the GROningen MOlecular Simulation software for (bio)molecular simulation. It contains more than 70 programs that can be used to prepare data for the production of

  20. The HADDOCK web server for data-driven biomolecular docking

    NARCIS (Netherlands)

    de Vries, S.J.|info:eu-repo/dai/nl/304837717; van Dijk, M.|info:eu-repo/dai/nl/325811113; Bonvin, A.M.J.J.|info:eu-repo/dai/nl/113691238

    2010-01-01

    Computational docking is the prediction or modeling of the three-dimensional structure of a biomolecular complex, starting from the structures of the individual molecules in their free, unbound form. HADDOC K is a popular docking program that takes a datadriven approach to docking, with support for

  1. Improvements to the APBS biomolecular solvation software suite.

    Science.gov (United States)

    Jurrus, Elizabeth; Engel, Dave; Star, Keith; Monson, Kyle; Brandi, Juan; Felberg, Lisa E; Brookes, David H; Wilson, Leighton; Chen, Jiahui; Liles, Karina; Chun, Minju; Li, Peter; Gohara, David W; Dolinsky, Todd; Konecny, Robert; Koes, David R; Nielsen, Jens Erik; Head-Gordon, Teresa; Geng, Weihua; Krasny, Robert; Wei, Guo-Wei; Holst, Michael J; McCammon, J Andrew; Baker, Nathan A

    2018-01-01

    The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that have provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses the three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this article, we discuss the models and capabilities that have recently been implemented within the APBS software package including a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory-based algorithm for determining pK a values, and an improved web-based visualization tool for viewing electrostatics. © 2017 The Protein Society.

  2. From dynamics to structure and function of model biomolecular systems

    NARCIS (Netherlands)

    Fontaine-Vive-Curtaz, F.

    2007-01-01

    The purpose of this thesis was to extend recent works on structure and dynamics of hydrogen bonded crystals to model biomolecular systems and biological processes. The tools that we have used are neutron scattering (NS) and density functional theory (DFT) and force field (FF) based simulation

  3. Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism

    Directory of Open Access Journals (Sweden)

    Tae-Hyoung Kim

    2017-01-01

    Full Text Available This paper studies the metaheuristic optimizer-based direct identification of a multiple-mode system consisting of a finite set of linear regression representations of subsystems. To this end, the concept of a multiple-mode linear regression model is first introduced, and its identification issues are established. A method for reducing the identification problem for multiple-mode models to an optimization problem is also described in detail. Then, to overcome the difficulties that arise because the formulated optimization problem is inherently ill-conditioned and nonconvex, the cyclic-network-topology-based constrained particle swarm optimizer (CNT-CPSO is introduced, and a concrete procedure for the CNT-CPSO-based identification methodology is developed. This scheme requires no prior knowledge of the mode transitions between subsystems and, unlike some conventional methods, can handle a large amount of data without difficulty during the identification process. This is one of the distinguishing features of the proposed method. The paper also considers an extension of the CNT-CPSO-based identification scheme that makes it possible to simultaneously obtain both the optimal parameters of the multiple submodels and a certain decision parameter involved in the mode transition criteria. Finally, an experimental setup using a DC motor system is established to demonstrate the practical usability of the proposed metaheuristic optimizer-based identification scheme for developing a multiple-mode linear regression model.

  4. Biomolecular strategies for cell surface engineering

    Science.gov (United States)

    Wilson, John Tanner

    Islet transplantation has emerged as a promising cell-based therapy for the treatment of diabetes, but its clinical efficacy remains limited by deleterious host responses that underlie islet destruction. In this dissertation, we describe the assembly of ultrathin conformal coatings that confer molecular-level control over the composition and biophysicochemical properties of the islet surface with implications for improving islet engraftment. Significantly, this work provides novel biomolecular strategies for cell surface engineering with broad biomedical and biotechnological applications in cell-based therapeutics and beyond. Encapsulation of cells and tissue offers a rational approach for attenuating deleterious host responses towards transplanted cells, but a need exists to develop cell encapsulation strategies that minimize transplant volume. Towards this end, we endeavored to generate nanothin films of diverse architecture with tunable properties on the extracellular surface of individual pancreatic islets through a process of layer-by-layer (LbL) self assembly. We first describe the formation of poly(ethylene glycol) (PEG)-rich conformal coatings on islets via LbL self assembly of poly(L-lysine)-g-PEG(biotin) and streptavidin. Multilayer thin films conformed to the geometrically and chemically heterogeneous islet surface, and could be assembled without loss of islet viability or function. Significantly, coated islets performed comparably to untreated controls in a murine model of allogenic intraportal islet transplantation, and, to our knowledge, this is the first study to report in vivo survival and function of nanoencapsulated cells or cell aggregates. Based on these findings, we next postulated that structurally similar PLL-g-PEG copolymers comprised of shorter PEG grafts might be used to initiate and propagate the assembly of polyelectrolyte multilayer (PEM) films on pancreatic islets, while simultaneously preserving islet viability. Through control of PLL

  5. Perspective: Watching low-frequency vibrations of water in biomolecular recognition by THz spectroscopy

    Science.gov (United States)

    Xu, Yao; Havenith, Martina

    2015-11-01

    Terahertz (THz) spectroscopy has turned out to be a powerful tool which is able to shed new light on the role of water in biomolecular processes. The low frequency spectrum of the solvated biomolecule in combination with MD simulations provides deep insights into the collective hydrogen bond dynamics on the sub-ps time scale. The absorption spectrum between 1 THz and 10 THz of solvated biomolecules is sensitive to changes in the fast fluctuations of the water network. Systematic studies on mutants of antifreeze proteins indicate a direct correlation between biological activity and a retardation of the (sub)-ps hydration dynamics at the protein binding site, i.e., a "hydration funnel." Kinetic THz absorption studies probe the temporal changes of THz absorption during a biological process, and give access to the kinetics of the coupled protein-hydration dynamics. When combined with simulations, the observed results can be explained in terms of a two-tier model involving a local binding and a long range influence on the hydration bond dynamics of the water around the binding site that highlights the significance of the changes in the hydration dynamics at recognition site for biomolecular recognition. Water is shown to assist molecular recognition processes.

  6. The influence of single neuron dynamics and network topology on time delay-induced multiple synchronous behaviors in inhibitory coupled network

    International Nuclear Information System (INIS)

    Zhao, Zhiguo; Gu, Huaguang

    2015-01-01

    Highlights: • Time delay-induced multiple synchronous behaviors was simulated in neuronal networks. • Multiple behaviors appear at time delays shorter than a bursting period of neurons. • The more spikes per burst of bursting, the more synchronous regions of time delay. • From regular to random via small-world networks, synchronous degree becomes weak. • An interpretation of the multiple behaviors and the influence of network are provided. - Abstract: Time delay induced-multiple synchronous behaviors are simulated in neuronal network composed of many inhibitory neurons and appear at different time delays shorter than a period of endogenous bursting of individual neurons. It is different from previous investigations wherein only one of multiple synchronous behaviors appears at time delay shorter than a period of endogenous firing and others appear at time delay longer than the period duration. The bursting patterns of the synchronous behaviors are identified based on the dynamics of an individual neuron stimulated by a signal similar to the inhibitory coupling current, which is applied at the decaying branch of a spike and suitable phase within the quiescent state of the endogenous bursting. If a burst of endogenous bursting contains more spikes, the synchronous behaviors appear at more regions of time delay. As the coupling strength increases, the multiple synchronous behaviors appear in a sequence because the different threshold of coupling current or strength is needed to achieve synchronous behaviors. From regular, to small-world, and to random networks, synchronous degree of the multiple synchronous behaviors becomes weak, and synchronous bursting patterns with lower spikes per burst disappear, which is properly interpreted by the difference of coupling current between neurons induced by different degree and the high threshold of coupling current to achieve synchronization for the absent synchronous bursting patterns. The results of the influence of

  7. Discrete event command and control for networked teams with multiple missions

    Science.gov (United States)

    Lewis, Frank L.; Hudas, Greg R.; Pang, Chee Khiang; Middleton, Matthew B.; McMurrough, Christopher

    2009-05-01

    During mission execution in military applications, the TRADOC Pamphlet 525-66 Battle Command and Battle Space Awareness capabilities prescribe expectations that networked teams will perform in a reliable manner under changing mission requirements, varying resource availability and reliability, and resource faults. In this paper, a Command and Control (C2) structure is presented that allows for computer-aided execution of the networked team decision-making process, control of force resources, shared resource dispatching, and adaptability to change based on battlefield conditions. A mathematically justified networked computing environment is provided called the Discrete Event Control (DEC) Framework. DEC has the ability to provide the logical connectivity among all team participants including mission planners, field commanders, war-fighters, and robotic platforms. The proposed data management tools are developed and demonstrated on a simulation study and an implementation on a distributed wireless sensor network. The results show that the tasks of multiple missions are correctly sequenced in real-time, and that shared resources are suitably assigned to competing tasks under dynamically changing conditions without conflicts and bottlenecks.

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

    Directory of Open Access Journals (Sweden)

    Jones Nick S

    2010-07-01

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

  9. A Systematic Scheme for Multiple Access in Ethernet Passive Optical Access Networks

    Science.gov (United States)

    Ma, Maode; Zhu, Yongqing; Hiang Cheng, Tee

    2005-11-01

    While backbone networks have experienced substantial changes in the last decade, access networks have not changed much. Recently, passive optical networks (PONs) seem to be ready for commercial deployment as access networks, due to the maturity of a number of enabling technologies. Among the PON technologies, Ethernet PON (EPON) standardized by the IEEE 802.3ah Ethernet in the First Mile (EFM) Task Force is the most attractive one because of its high speed, low cost, familiarity, interoperability, and low overhead. In this paper, we consider the issue of upstream channel sharing in the EPONs. We propose a novel multiple-access control scheme to provide bandwidth-guaranteed service for high-demand customers, while providing best effort service to low-demand customers according to the service level agreement (SLA). The analytical and simulation results prove that the proposed scheme performs best in what it is designed to do compared to another well-known scheme that has not considered providing differentiated services. With business customers preferring premium services with guaranteed bandwidth and residential users preferring low-cost best effort services, our scheme could benefit both groups of subscribers, as well as the operators.

  10. Three-Way Channels With Multiple Unicast Sessions: Capacity Approximation via Network Transformation

    KAUST Repository

    Chaaban, Anas

    2016-09-28

    A network of three nodes mutually communicating with each other is studied. This multi-way network is a suitable model for three-user device-to-device communications. The main goal of this paper is to characterize the capacity region of the underlying Gaussian three-way channel (3WC) within a constant gap. To this end, a capacity outer bound is derived using cut-set bounds and genie-aided bounds. For achievability, the 3WC is first transformed into an equivalent star channel. This latter is then decomposed into a set of “successive” sub-channels, leading to a sub-channel allocation problem. Using backward decoding, interference neutralization, and known results on the capacity of the star-channel relying of physical-layer network coding, an achievable rate region for the 3WC is obtained. It is then shown that the achievable rate region is within a constant gap of the developed outer bound, leading to the desired capacity approximation. Interestingly, in contrast to the Gaussian two-way channel (TWC), adaptation is necessary in the 3WC. Furthermore, message splitting is another ingredient of the developed scheme for the 3WC, which is not required in the TWC. The two setups are, however, similar in terms of their sum-capacity pre-log, which is equal to 2. Finally, some interesting networks and their approximate capacities are recovered as special cases of the 3WC, such as the cooperative broadcast channel and multiple access channel.

  11. Symbolic dynamics and synchronization of coupled map networks with multiple delays

    International Nuclear Information System (INIS)

    Atay, Fatihcan M.; Jalan, Sarika; Jost, Juergen

    2010-01-01

    We use symbolic dynamics to study discrete-time dynamical systems with multiple time delays. We exploit the concept of avoiding sets, which arise from specific non-generating partitions of the phase space and restrict the occurrence of certain symbol sequences related to the characteristics of the dynamics. In particular, we show that the resulting forbidden sequences are closely related to the time delays in the system. We present two applications to coupled map lattices, namely (1) detecting synchronization and (2) determining unknown values of the transmission delays in networks with possibly directed and weighted connections and measurement noise. The method is applicable to multi-dimensional as well as set-valued maps, and to networks with time-varying delays and connection structure.

  12. A Neural Network Model to Learn Multiple Tasks under Dynamic Environments

    Science.gov (United States)

    Tsumori, Kenji; Ozawa, Seiichi

    When environments are dynamically changed for agents, the knowledge acquired in an environment might be useless in future. In such dynamic environments, agents should be able to not only acquire new knowledge but also modify old knowledge in learning. However, modifying all knowledge acquired before is not efficient because the knowledge once acquired may be useful again when similar environment reappears and some knowledge can be shared among different environments. To learn efficiently in such environments, we propose a neural network model that consists of the following modules: resource allocating network, long-term & short-term memory, and environment change detector. We evaluate the model under a class of dynamic environments where multiple function approximation tasks are sequentially given. The experimental results demonstrate that the proposed model possesses stable incremental learning, accurate environmental change detection, proper association and recall of old knowledge, and efficient knowledge transfer.

  13. Multiple Time Series Forecasting Using Quasi-Randomized Functional Link Neural Networks

    Directory of Open Access Journals (Sweden)

    Thierry Moudiki

    2018-03-01

    Full Text Available We are interested in obtaining forecasts for multiple time series, by taking into account the potential nonlinear relationships between their observations. For this purpose, we use a specific type of regression model on an augmented dataset of lagged time series. Our model is inspired by dynamic regression models (Pankratz 2012, with the response variable’s lags included as predictors, and is known as Random Vector Functional Link (RVFL neural networks. The RVFL neural networks have been successfully applied in the past, to solving regression and classification problems. The novelty of our approach is to apply an RVFL model to multivariate time series, under two separate regularization constraints on the regression parameters.

  14. Use of multiple dispersal pathways facilitates amphibian persistence in stream networks

    Science.gov (United States)

    Campbell, Grant E.H.; Nichols, J.D.; Lowe, W.H.; Fagan, W.F.

    2010-01-01

    Although populations of amphibians are declining worldwide, there is no evidence that salamanders occupying small streams are experiencing enigmatic declines, and populations of these species seem stable. Theory predicts that dispersal through multiple pathways can stabilize populations, preventing extinction in habitat networks. However, empirical data to support this prediction are absent for most species, especially those at risk of decline. Our mark-recapture study of stream salamanders reveals both a strong upstream bias in dispersal and a surprisingly high rate of overland dispersal to adjacent headwater streams. This evidence of route-dependent variation in dispersal rates suggests a spatial mechanism for population stability in headwater-stream salamanders. Our results link the movement behavior of stream salamanders to network topology, and they underscore the importance of identifying and protecting critical dispersal pathways when addressing region-wide population declines.

  15. Use of multiple dispersal pathways facilitates amphibian persistence in stream networks.

    Science.gov (United States)

    Campbell Grant, Evan H; Nichols, James D; Lowe, Winsor H; Fagan, William F

    2010-04-13

    Although populations of amphibians are declining worldwide, there is no evidence that salamanders occupying small streams are experiencing enigmatic declines, and populations of these species seem stable. Theory predicts that dispersal through multiple pathways can stabilize populations, preventing extinction in habitat networks. However, empirical data to support this prediction are absent for most species, especially those at risk of decline. Our mark-recapture study of stream salamanders reveals both a strong upstream bias in dispersal and a surprisingly high rate of overland dispersal to adjacent headwater streams. This evidence of route-dependent variation in dispersal rates suggests a spatial mechanism for population stability in headwater-stream salamanders. Our results link the movement behavior of stream salamanders to network topology, and they underscore the importance of identifying and protecting critical dispersal pathways when addressing region-wide population declines.

  16. Novel global robust stability criteria for interval neural networks with multiple time-varying delays

    International Nuclear Information System (INIS)

    Xu Shengyuan; Lam, James; Ho, Daniel W.C.

    2005-01-01

    This Letter is concerned with the problem of robust stability analysis for interval neural networks with multiple time-varying delays and parameter uncertainties. The parameter uncertainties are assumed to be bounded in given compact sets and the activation functions are supposed to be bounded and globally Lipschitz continuous. A sufficient condition is obtained by means of Lyapunov functionals, which guarantees the existence, uniqueness and global asymptotic stability of the delayed neural network for all admissible uncertainties. This condition is in terms of a linear matrix inequality (LMI), which can be easily checked by using recently developed algorithms in solving LMIs. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method

  17. A Suboptimal Power-Saving Transmission Scheme in Multiple Component Carrier Networks

    Science.gov (United States)

    Chung, Yao-Liang; Tsai, Zsehong

    Power consumption due to transmissions in base stations (BSs) has been a major contributor to communication-related CO2 emissions. A power optimization model is developed in this study with respect to radio resource allocation and activation in a multiple Component Carrier (CC) environment. We formulate and solve the power-minimization problem of the BS transceivers for multiple-CC networks with carrier aggregation, while maintaining the overall system and respective users' utilities above minimum levels. The optimized power consumption based on this model can be viewed as a lower bound of that of other algorithms employed in practice. A suboptimal scheme with low computation complexity is proposed. Numerical results show that the power consumption of our scheme is much better than that of the conventional one in which all CCs are always active, if both schemes maintain the same required utilities.

  18. A distributed Synchronous reservation multiple access control protocol for mobile Ad hoc networks

    Institute of Scientific and Technical Information of China (English)

    ZHANG Yanling; SUN Xianpu; LI Jiandong

    2007-01-01

    This study proposes a new multiple access control protocol named distributed synchronous reservation multiple access control protocol.in which the hidden and exposed terminal problems are solved,and the quality of service(QoS)requirements for real-time traffic are guaranteed.The protocol is founded on time division multiplex address and a different type of traffic is assigned to difierent priority,according to which a node should compete for and reserve the free slots in a different method.Moreover,there is a reservation acknowledgement process before data transmit in each reserved slot,so that the intruded terminal problem is solved.The throughput and average packets drop probability of this protocol are analyzed and simulated in a fully connected network.the results of which indicate that this protocol is efficient enough to support the real-time traffic.and it is more suitable to MANETs.

  19. Power Allocation in Multiple Access Networks: Implementation Aspects via Verhulst and Perron-Frobenius Models

    Directory of Open Access Journals (Sweden)

    Fábio Engel de Camargo

    2012-11-01

    Full Text Available In this work, the Verhulst model and the Perron-Frobenius theorem are applied on the power control problem which is a concern in multiple access communication networks due to the multiple access interference. This paper deals with the performance versus complexity tradeoff of both power control algorithm (PCA, as well as highlights the computational cost aspects regarding the implementability of distributed PCA (DPCA version for both algorithms. As a proof-of-concept the DPCA implementation is carried out deploying a commercial point-floating DSP platform. Numerical results in terms of DSP cycles and computational time as well indicate a feasibility of implementing the PCA-Verhulst model in 2G and 3G cellular systems; b high computational cost for the PCA-Perron-Frobenius model.

  20. A genetic algorithm for multiple relay selection in two-way relaying cognitive radio networks

    KAUST Repository

    Alsharoa, Ahmad M.

    2013-09-01

    In this paper, we investigate a multiple relay selection scheme for two-way relaying cognitive radio networks where primary users and secondary users operate on the same frequency band. More specifically, cooperative relays using Amplifyand- Forward (AF) protocol are optimally selected to maximize the sum rate of the secondary users without degrading the Quality of Service (QoS) of the primary users by respecting a tolerated interference threshold. A strong optimization tool based on genetic algorithm is employed to solve our formulated optimization problem where discrete relay power levels are considered. Our simulation results show that the practical heuristic approach achieves almost the same performance of the optimal multiple relay selection scheme either with discrete or continuous power distributions. Copyright © 2013 by the Institute of Electrical and Electronic Engineers, Inc.

  1. A low complexity algorithm for multiple relay selection in two-way relaying Cognitive Radio networks

    KAUST Repository

    Alsharoa, Ahmad M.

    2013-06-01

    In this paper, a multiple relay selection scheme for two-way relaying cognitive radio network is investigated. We consider a cooperative Cognitive Radio (CR) system with spectrum sharing scenario using Amplify-and-Forward (AF) protocol, where licensed users and unlicensed users operate on the same frequency band. The main objective is to maximize the sum rate of the unlicensed users allowed to share the spectrum with the licensed users by respecting a tolerated interference threshold. A practical low complexity heuristic approach is proposed to solve our formulated optimization problem. Selected numerical results show that the proposed algorithm reaches a performance close to the performance of the optimal multiple relay selection scheme either with discrete or continuous power distributions while providing a considerable saving in terms of computational complexity. In addition, these results show that our proposed scheme significantly outperforms the single relay selection scheme. © 2013 IEEE.

  2. Networking Multiple Autonomous Air and Ocean Vehicles for Oceanographic Research and Monitoring

    Science.gov (United States)

    McGillivary, P. A.; Borges de Sousa, J.; Rajan, K.

    2013-12-01

    Autonomous underwater and surface vessels (AUVs and ASVs) are coming into wider use as components of oceanographic research, including ocean observing systems. Unmanned airborne vehicles (UAVs) are now available at modest cost, allowing multiple UAVs to be deployed with multiple AUVs and ASVs. For optimal use good communication and coordination among vehicles is essential. We report on the use of multiple AUVs networked in communication with multiple UAVs. The UAVs are augmented by inferential reasoning software developed at MBARI that allows UAVs to recognize oceanographic fronts and change their navigation and control. This in turn allows UAVs to automatically to map frontal features, as well as to direct AUVs and ASVs to proceed to such features and conduct sampling via onboard sensors to provide validation for airborne mapping. ASVs can also act as data nodes for communication between UAVs and AUVs, as well as collecting data from onboard sensors, while AUVs can sample the water column vertically. This allows more accurate estimation of phytoplankton biomass and productivity, and can be used in conjunction with UAV sampling to determine air-sea flux of gases (e.g. CO2, CH4, DMS) affecting carbon budgets and atmospheric composition. In particular we describe tests in July 2013 conducted off Sesimbra, Portugal in conjunction with the Portuguese Navy by the University of Porto and MBARI with the goal of tracking large fish in the upper water column with coordinated air/surface/underwater measurements. A thermal gradient was observed in the infrared by a low flying UAV, which was used to dispatch an AUV to obtain ground truth to demonstrate the event-response capabilities using such autonomous platforms. Additional field studies in the future will facilitate integration of multiple unmanned systems into research vessel operations. The strength of hardware and software tools described in this study is to permit fundamental oceanographic measurements of both ocean

  3. Estimating Single and Multiple Target Locations Using K-Means Clustering with Radio Tomographic Imaging in Wireless Sensor Networks

    Science.gov (United States)

    2015-03-26

    clustering is an algorithm that has been used in data mining applications such as machine learning applications , pattern recognition, hyper-spectral imagery...42 3.7.2 Application of K-means Clustering . . . . . . . . . . . . . . . . . 42 3.8 Experiment Design...Tomographic Imaging WLAN Wireless Local Area Networks WSN Wireless Sensor Network xx ESTIMATING SINGLE AND MULTIPLE TARGET LOCATIONS USING K-MEANS CLUSTERING

  4. Nonadditivity of quantum and classical capacities for entanglement breaking multiple-access channels and the butterfly network

    International Nuclear Information System (INIS)

    Grudka, Andrzej; Horodecki, Pawel

    2010-01-01

    We analyze quantum network primitives which are entanglement breaking. We show superadditivity of quantum and classical capacity regions for quantum multiple-access channels and the quantum butterfly network. Since the effects are especially visible at high noise they suggest that quantum information effects may be particularly helpful in the case of the networks with occasional high noise rates. The present effects provide a qualitative borderline between superadditivities of bipartite and multipartite systems.

  5. Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes.

    Science.gov (United States)

    Achana, Felix A; Cooper, Nicola J; Bujkiewicz, Sylwia; Hubbard, Stephanie J; Kendrick, Denise; Jones, David R; Sutton, Alex J

    2014-07-21

    Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on

  6. Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

    Science.gov (United States)

    Rai, Man Mohan

    2006-01-01

    Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more

  7. White matter tract network disruption explains reduced conscientiousness in multiple sclerosis.

    Science.gov (United States)

    Fuchs, Tom A; Dwyer, Michael G; Kuceyeski, Amy; Choudhery, Sanjeevani; Carolus, Keith; Li, Xian; Mallory, Matthew; Weinstock-Guttman, Bianca; Jakimovski, Dejan; Ramasamy, Deepa; Zivadinov, Robert; Benedict, Ralph H B

    2018-05-08

    Quantifying white matter (WM) tract disruption in people with multiple sclerosis (PwMS) provides a novel means for investigating the relationship between defective network connectivity and clinical markers. PwMS exhibit perturbations in personality, where decreased Conscientiousness is particularly prominent. This trait deficit influences disease trajectory and functional outcomes such as work capacity. We aimed to identify patterns of WM tract disruption related to decreased Conscientiousness in PwMS. Personality assessment and brain MRI were obtained in 133 PwMS and 49 age- and sex-matched healthy controls (HC). Lesion maps were applied to determine the severity of WM tract disruption between pairs of gray matter regions. Next, the Network-Based-Statistics tool was applied to identify structural networks whose disruption negatively correlates with Conscientiousness. Finally, to determine whether these networks explain unique variance above conventional MRI measures and cognition, regression models were applied controlling for age, sex, brain volume, T2-lesion volume, and cognition. Relative to HCs, PwMS exhibited lower Conscientiousness and slowed cognitive processing speed (p = .025, p = .006). Lower Conscientiousness in PwMS was significantly associated with WM tract disruption between frontal, frontal-parietal, and frontal-cingulate pathways in the left (p = .02) and right (p = .01) hemisphere. The mean disruption of these pathways explained unique additive variance in Conscientiousness, after accounting for conventional MRI markers of pathology and cognition (ΔR 2  = .049, p = .029). Damage to WM tracts between frontal, frontal-parietal, and frontal-cingulate cortical regions is significantly correlated with reduced Conscientiousness in PwMS. Tract disruption within these networks explains decreased Conscientiousness observed in PwMS as compared with HCs. © 2018 Wiley Periodicals, Inc.

  8. Dynamic and label-free high-throughput detection of biomolecular interactions based on phase-shift interferometry

    Science.gov (United States)

    Li, Qiang; Huang, Guoliang; Gan, Wupeng; Chen, Shengyi

    2009-08-01

    Biomolecular interactions can be detected by many established technologies such as fluorescence imaging, surface plasmon resonance (SPR)[1-4], interferometry and radioactive labeling of the analyte. In this study, we have designed and constructed a label-free, real-time sensing platform and its operating imaging instrument that detects interactions using optical phase differences from the accumulation of biological material on solid substrates. This system allows us to monitor biomolecular interactions in real time and quantify concentration changes during micro-mixing processes by measuring the changes of the optical path length (OPD). This simple interferometric technology monitors the optical phase difference resulting from accumulated biomolecular mass. A label-free protein chip that forms a 4×4 probe array was designed and fabricated using a commercial microarray robot spotter on solid substrates. Two positive control probe lines of BSA (Bovine Serum Albumin) and two experimental human IgG and goat IgG was used. The binding of multiple protein targets was performed and continuously detected by using this label-free and real-time sensing platform.

  9. A space weather forecasting system with multiple satellites based on a self-recognizing network.

    Science.gov (United States)

    Tokumitsu, Masahiro; Ishida, Yoshiteru

    2014-05-05

    This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

  10. Cross-Layer Design for Two-Way Relaying Networks with Multiple Antennas

    Directory of Open Access Journals (Sweden)

    zhuo wu

    2015-10-01

    Full Text Available In this paper, we developed a cross-layer design for two-way relaying (TWR networks with multiple antennas, where two single antenna source nodes exchange information with the aid of one multiple antenna relay node. The proposed cross-layer design considers adaptive modulation (AM and space-time block coding (STBC at the physical layer with an automatic repeat request (ARQ protocol at the data link layer, in order to maximize the spectral efficiency under specific delay and packet error ratio (PER constraints. An MMSE-interference cancellation (IC receiver is employed at the relay node, to remove the interference in the fist phase of the TWR transmission. The transmission mode is updated for each phase of the TWR transmission on a frame-by-frame basis, to match the time-varying channel conditions and exploit the system performance and throughput gain. Simulation results show that retransmission at the data link layer could alleviate rigorous error-control requirements at the physical layer, and thereby allows higher data transmission. As a result, cross-layer design helps to achieve considerable system spectral efficiency gain for TWR networks, compared to those without cross-layer design.

  11. Real-time multiple networked viewer capability of the DIII-D EC data acquisition system

    International Nuclear Information System (INIS)

    Ponce, D.; Gorelov, I.A.; Chiu, H.K.; Baity, F.W.

    2005-01-01

    A data acquisition system (DAS) which permits real-time viewing by multiple locally networked operators is being implemented for the electron cyclotron (EC) heating and current drive system at DIII-D. The DAS is expected to demonstrate performance equivalent to standalone oscilloscopes. Participation by remote viewers, including throughout the greater DIII-D facility, can also be incorporated. The real-time system uses one computer-controlled DAS per gyrotron. The DAS computers send their data to a central data server using individual and dedicated 200 Mbps fully duplexed Ethernet connections. The server has a dedicated 10 krpm hard drive for each gyrotron DAS. Selected channels can then be reprocessed and distributed to viewers over a standard local area network (LAN). They can also be bridged from the LAN to the internet. Calculations indicate that the hardware will support real-time writing of each channel at full resolution to the server hard drives. The data will be re-sampled for distribution to multiple viewers over the LAN in real-time. The hardware for this system is in place. The software is under development. This paper will present the design details and up-to-date performance metrics of the system

  12. Sequential interrogation of multiple FBG sensors using LPG modulation and an artificial neural network

    International Nuclear Information System (INIS)

    Basu, Mainak; Ghorai, S K

    2015-01-01

    Interrogating multiple fiber Bragg gratings (FBG) requires highly sensitive spectrum scanning equipment such as optical spectrum analyzers, tunable filters, acousto-optic tunable filters etc, which are expensive, bulky and time consuming. In this paper, we present a new approach for multiple FBG sensor interrogation using long-period gratings and an artificial neural network. The reflection spectra of the multiplexed FBGs are modulated by two long period gratings separately and the modulated optical intensities were detected by two photodetectors. The outputs of the detectors are then used as input in a previously trained artificial neural network to interrogate the FBG sensors. Simulations have been performed to determine the strain and wavelength shift using two and four sensors. The interrogation system has also been demonstrated experimentally for two sensors using simply supported beams in the range of 0–350 μstrain. The proposed interrogation scheme has been found to identify the perturbed FBG, and to determine strain and wavelength shift with reasonable accuracy. (paper)

  13. U.S. Department of Defense Multiple-Parameter Biodosimetry Network

    International Nuclear Information System (INIS)

    Blakely, William F.; Hoefer, Matthew H.; Huff, L. Andrew; Romanyukha, Alexander; Hayes, Selena M.; Williams, Anthony; Sharp, Thad; Reyes, Ricardo A.; Stewart, H. Michael Jr

    2016-01-01

    The U.S. Department of Defense (US-DOD) service members are at risk of exposure to ionizing radiation due to radiation accidents, terrorist attacks and national defense activities. The use of biodosimetry is a standard of care for the triage and treatment of radiation injuries. Resources and procedures need to be established to implement a multiple-parameter biodosimetry system coupled with expert medial guidance to provide an integrated radiation diagnostic system to meet US-DOD requirements. Current US-DOD biodosimetry capabilities were identified and recommendations to fill the identified gaps are provided. A US-DOD Multi-parametric Biodosimetry Network, based on the expertise that resides at the Armed Forces Radiobiology Research Institute and the Naval Dosimetry Center, was designed. This network based on the use of multiple biodosimetry modalities would provide diagnostic and triage capabilities needed to meet US-DOD requirements. These are not available with sufficient capacity elsewhere but could be needed urgently after a major radiological/nuclear event. (authors)

  14. A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network

    Directory of Open Access Journals (Sweden)

    Masahiro Tokumitsu

    2014-05-01

    Full Text Available This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV. The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

  15. Channel capacity of TDD-OFDM-MIMO for multiple access points in a wireless single-frequency-network

    DEFF Research Database (Denmark)

    Takatori, Y.; Fitzek, Frank; Tsunekawa, K.

    2005-01-01

    MIMO data transmission scheme, which combines Single-Frequency-Network (SFN) with TDD-OFDM-MIMO applied for wireless LAN networks. In our proposal, we advocate to use SFN for multiple access points (MAP) MIMO data transmission. The goal of this approach is to achieve very high channel capacity in both......The multiple-input-multiple-output (MIMO) technique is the most attractive candidate to improve the spectrum efficiency in the next generation wireless communication systems. However, the efficiency of MIMO techniques reduces in the line of sight (LOS) environments. In this paper, we propose a new...

  16. Parameter Diversity Induced Multiple Spatial Coherence Resonances and Spiral Waves in Neuronal Network with and Without Noise

    International Nuclear Information System (INIS)

    Li Yuye; Jia Bing; Gu Huaguang; An Shucheng

    2012-01-01

    Diversity in the neurons and noise are inevitable in the real neuronal network. In this paper, parameter diversity induced spiral waves and multiple spatial coherence resonances in a two-dimensional neuronal network without or with noise are simulated. The relationship between the multiple resonances and the multiple transitions between patterns of spiral waves are identified. The coherence degrees induced by the diversity are suppressed when noise is introduced and noise density is increased. The results suggest that natural nervous system might profit from both parameter diversity and noise, provided a possible approach to control formation and transition of spiral wave by the cooperation between the diversity and noise. (general)

  17. Non-Orthogonal Multiple Access for Large-Scale 5G Networks: Interference Aware Design

    KAUST Repository

    Ali, Konpal S.

    2017-09-18

    Non-orthogonal multiple access (NOMA) is promoted as a key component of 5G cellular networks. As the name implies, NOMA operation introduces intracell interference (i.e., interference arising within the cell) to the cellular operation. The intracell interference is managed by careful NOMA design (e.g., user clustering and resource allocation) along with successive interference cancellation. However, most of the proposed NOMA designs are agnostic to intercell interference (i.e., interference from outside the cell), which is a major performance limiting parameter in 5G networks. This article sheds light on the drastic negative-impact of intercell interference on the NOMA performance and advocates interference-aware NOMA design that jointly accounts for both intracell and intercell interference. To this end, a case study for fair NOMA operation is presented and intercell interference mitigation techniques for NOMA networks are discussed. This article also investigates the potential of integrating NOMA with two important 5G transmission schemes, namely, full duplex and device-to-device communication. This is important since the ambitious performance defined by the 3rd Generation Partnership Project (3GPP) for 5G is foreseen to be realized via seamless integration of several new technologies and transmission techniques.

  18. Network hydraulics inclusion in water quality event detection using multiple sensor stations data.

    Science.gov (United States)

    Oliker, Nurit; Ostfeld, Avi

    2015-09-01

    Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. A Network Pharmacology Approach to Uncover the Multiple Mechanisms of Hedyotis diffusa Willd. on Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Xinkui Liu

    2018-01-01

    Full Text Available Background. As one of the most frequently diagnosed cancer diseases globally, colorectal cancer (CRC remains an important cause of cancer-related death. Although the traditional Chinese herb Hedyotis diffusa Willd. (HDW has been proven to be effective for treating CRC in clinical practice, its definite mechanisms have not been completely deciphered. Objective. The aim of our research is to systematically explore the multiple mechanisms of HDW on CRC. Methods. This study adopted the network pharmacology approach, which was mainly composed of active component gathering, target prediction, CRC gene collection, network analysis, and gene enrichment analysis. Results. The network analysis showed that 10 targets might be the therapeutic targets of HDW on CRC, namely, HRAS, PIK3CA, KRAS, TP53, APC, BRAF, GSK3B, CDK2, AKT1, and RAF1. The gene enrichment analysis implied that HDW probably benefits patients with CRC by modulating pathways related to cancers, infectious diseases, endocrine system, immune system, nervous system, signal transduction, cellular community, and cell motility. Conclusions. This study partially verified and predicted the pharmacological and molecular mechanism of HDW against CRC from a holistic perspective, which will also lay a foundation for the further experimental research and clinical rational application of HDW.

  20. Neural Networks for Segregation of Multiple Objects: Visual Figure-Ground Separation and Auditory Pitch Perception.

    Science.gov (United States)

    Wyse, Lonce

    An important component of perceptual object recognition is the segmentation into coherent perceptual units of the "blooming buzzing confusion" that bombards the senses. The work presented herein develops neural network models of some key processes of pre-attentive vision and audition that serve this goal. A neural network model, called an FBF (Feature -Boundary-Feature) network, is proposed for automatic parallel separation of multiple figures from each other and their backgrounds in noisy images. Figure-ground separation is accomplished by iterating operations of a Boundary Contour System (BCS) that generates a boundary segmentation of a scene, and a Feature Contour System (FCS) that compensates for variable illumination and fills-in surface properties using boundary signals. A key new feature is the use of the FBF filling-in process for the figure-ground separation of connected regions, which are subsequently more easily recognized. The new CORT-X 2 model is a feed-forward version of the BCS that is designed to detect, regularize, and complete boundaries in up to 50 percent noise. It also exploits the complementary properties of on-cells and off -cells to generate boundary segmentations and to compensate for boundary gaps during filling-in. In the realm of audition, many sounds are dominated by energy at integer multiples, or "harmonics", of a fundamental frequency. For such sounds (e.g., vowels in speech), the individual frequency components fuse, so that they are perceived as one sound source with a pitch at the fundamental frequency. Pitch is integral to separating auditory sources, as well as to speaker identification and speech understanding. A neural network model of pitch perception called SPINET (SPatial PItch NETwork) is developed and used to simulate a broader range of perceptual data than previous spectral models. The model employs a bank of narrowband filters as a simple model of basilar membrane mechanics, spectral on-center off-surround competitive

  1. Multimodal wireless sensor network-based ambient assisted living in real homes with multiple residents.

    Science.gov (United States)

    Tunca, Can; Alemdar, Hande; Ertan, Halil; Incel, Ozlem Durmaz; Ersoy, Cem

    2014-05-30

    Human activity recognition and behavior monitoring in a home setting using wireless sensor networks (WSNs) provide a great potential for ambient assisted living (AAL) applications, ranging from health and wellbeing monitoring to resource consumption monitoring. However, due to the limitations of the sensor devices, challenges in wireless communication and the challenges in processing large amounts of sensor data in order to recognize complex human activities, WSN-based AAL systems are not effectively integrated in the home environment. Additionally, given the variety of sensor types and activities, selecting the most suitable set of sensors in the deployment is an important task. In order to investigate and propose solutions to such challenges, we introduce a WSN-based multimodal AAL system compatible for homes with multiple residents. Particularly, we focus on the details of the system architecture, including the challenges of sensor selection, deployment, networking and data collection and provide guidelines for the design and deployment of an effective AAL system. We also present the details of the field study we conducted, using the systems deployed in two different real home environments with multiple residents. With these systems, we are able to collect ambient sensor data from multiple homes. This data can be used to assess the wellbeing of the residents and identify deviations from everyday routines, which may be indicators of health problems. Finally, in order to elaborate on the possible applications of the proposed AAL system and to exemplify directions for processing the collected data, we provide the results of several human activity inference experiments, along with examples on how such results could be interpreted. We believe that the experiences shared in this work will contribute towards accelerating the acceptance of WSN-based AAL systems in the home setting.

  2. Multimodal Wireless Sensor Network-Based Ambient Assisted Living in Real Homes with Multiple Residents

    Directory of Open Access Journals (Sweden)

    Can Tunca

    2014-05-01

    Full Text Available Human activity recognition and behavior monitoring in a home setting using wireless sensor networks (WSNs provide a great potential for ambient assisted living (AAL applications, ranging from health and wellbeing monitoring to resource consumption monitoring. However, due to the limitations of the sensor devices, challenges in wireless communication and the challenges in processing large amounts of sensor data in order to recognize complex human activities, WSN-based AAL systems are not effectively integrated in the home environment. Additionally, given the variety of sensor types and activities, selecting the most suitable set of sensors in the deployment is an important task. In order to investigate and propose solutions to such challenges, we introduce a WSN-based multimodal AAL system compatible for homes with multiple residents. Particularly, we focus on the details of the system architecture, including the challenges of sensor selection, deployment, networking and data collection and provide guidelines for the design and deployment of an effective AAL system. We also present the details of the field study we conducted, using the systems deployed in two different real home environments with multiple residents. With these systems, we are able to collect ambient sensor data from multiple homes. This data can be used to assess the wellbeing of the residents and identify deviations from everyday routines, which may be indicators of health problems. Finally, in order to elaborate on the possible applications of the proposed AAL system and to exemplify directions for processing the collected data, we provide the results of several human activity inference experiments, along with examples on how such results could be interpreted. We believe that the experiences shared in this work will contribute towards accelerating the acceptance of WSN-based AAL systems in the home setting.

  3. Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach.

    Science.gov (United States)

    Valverde, Sergi; Cabezas, Mariano; Roura, Eloy; González-Villà, Sandra; Pareto, Deborah; Vilanova, Joan C; Ramió-Torrentà, Lluís; Rovira, Àlex; Oliver, Arnau; Lladó, Xavier

    2017-07-15

    In this paper, we present a novel automated method for White Matter (WM) lesion segmentation of Multiple Sclerosis (MS) patient images. Our approach is based on a cascade of two 3D patch-wise convolutional neural networks (CNN). The first network is trained to be more sensitive revealing possible candidate lesion voxels while the second network is trained to reduce the number of misclassified voxels coming from the first network. This cascaded CNN architecture tends to learn well from a small (n≤35) set of labeled data of the same MRI contrast, which can be very interesting in practice, given the difficulty to obtain manual label annotations and the large amount of available unlabeled Magnetic Resonance Imaging (MRI) data. We evaluate the accuracy of the proposed method on the public MS lesion segmentation challenge MICCAI2008 dataset, comparing it with respect to other state-of-the-art MS lesion segmentation tools. Furthermore, the proposed method is also evaluated on two private MS clinical datasets, where the performance of our method is also compared with different recent public available state-of-the-art MS lesion segmentation methods. At the time of writing this paper, our method is the best ranked approach on the MICCAI2008 challenge, outperforming the rest of 60 participant methods when using all the available input modalities (T1-w, T2-w and FLAIR), while still in the top-rank (3rd position) when using only T1-w and FLAIR modalities. On clinical MS data, our approach exhibits a significant increase in the accuracy segmenting of WM lesions when compared with the rest of evaluated methods, highly correlating (r≥0.97) also with the expected lesion volume. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Autapse-induced multiple stochastic resonances in a modular neuronal network

    Science.gov (United States)

    Yang, XiaoLi; Yu, YanHu; Sun, ZhongKui

    2017-08-01

    This study investigates the nontrivial effects of autapse on stochastic resonance in a modular neuronal network subjected to bounded noise. The resonance effect of autapse is detected by imposing a self-feedback loop with autaptic strength and autaptic time delay to each constituent neuron. Numerical simulations have demonstrated that bounded noise with the proper level of amplitude can induce stochastic resonance; moreover, the noise induced resonance dynamics can be significantly shaped by the autapse. In detail, for a specific range of autaptic strength, multiple stochastic resonances can be induced when the autaptic time delays are appropriately adjusted. These appropriately adjusted delays are detected to nearly approach integer multiples of the period of the external weak signal when the autaptic strength is very near zero; otherwise, they do not match the period of the external weak signal when the autaptic strength is slightly greater than zero. Surprisingly, in both cases, the differences between arbitrary two adjacent adjusted autaptic delays are always approximately equal to the period of the weak signal. The phenomenon of autaptic delay induced multiple stochastic resonances is further confirmed to be robust against the period of the external weak signal and the intramodule probability of subnetwork. These findings could have important implications for weak signal detection and information propagation in realistic neural systems.

  5. Biomolecular structure refinement using the GROMOS simulation software

    International Nuclear Information System (INIS)

    Schmid, Nathan; Allison, Jane R.; Dolenc, Jožica; Eichenberger, Andreas P.; Kunz, Anna-Pitschna E.; Gunsteren, Wilfred F. van

    2011-01-01

    For the understanding of cellular processes the molecular structure of biomolecules has to be accurately determined. Initial models can be significantly improved by structure refinement techniques. Here, we present the refinement methods and analysis techniques implemented in the GROMOS software for biomolecular simulation. The methodology and some implementation details of the computation of NMR NOE data, 3 J-couplings and residual dipolar couplings, X-ray scattering intensities from crystals and solutions and neutron scattering intensities used in GROMOS is described and refinement strategies and concepts are discussed using example applications. The GROMOS software allows structure refinement combining different types of experimental data with different types of restraining functions, while using a variety of methods to enhance conformational searching and sampling and the thermodynamically calibrated GROMOS force field for biomolecular simulation.

  6. Biomolecular structure refinement using the GROMOS simulation software

    Energy Technology Data Exchange (ETDEWEB)

    Schmid, Nathan; Allison, Jane R.; Dolenc, Jozica; Eichenberger, Andreas P.; Kunz, Anna-Pitschna E.; Gunsteren, Wilfred F. van, E-mail: wfvgn@igc.phys.chem.ethz.ch [Swiss Federal Institute of Technology ETH, Laboratory of Physical Chemistry (Switzerland)

    2011-11-15

    For the understanding of cellular processes the molecular structure of biomolecules has to be accurately determined. Initial models can be significantly improved by structure refinement techniques. Here, we present the refinement methods and analysis techniques implemented in the GROMOS software for biomolecular simulation. The methodology and some implementation details of the computation of NMR NOE data, {sup 3}J-couplings and residual dipolar couplings, X-ray scattering intensities from crystals and solutions and neutron scattering intensities used in GROMOS is described and refinement strategies and concepts are discussed using example applications. The GROMOS software allows structure refinement combining different types of experimental data with different types of restraining functions, while using a variety of methods to enhance conformational searching and sampling and the thermodynamically calibrated GROMOS force field for biomolecular simulation.

  7. Physics at the biomolecular interface fundamentals for molecular targeted therapy

    CERN Document Server

    Fernández, Ariel

    2016-01-01

    This book focuses primarily on the role of interfacial forces in understanding biological phenomena at the molecular scale. By providing a suitable statistical mechanical apparatus to handle the biomolecular interface, the book becomes uniquely positioned to address core problems in molecular biophysics. It highlights the importance of interfacial tension in delineating a solution to the protein folding problem, in unravelling the physico-chemical basis of enzyme catalysis and protein associations, and in rationally designing molecular targeted therapies. Thus grounded in fundamental science, the book develops a powerful technological platform for drug discovery, while it is set to inspire scientists at any level in their careers determined to address the major challenges in molecular biophysics. The acknowledgment of how exquisitely the structure and dynamics of proteins and their aqueous environment are related attests to the overdue recognition that biomolecular phenomena cannot be effectively understood w...

  8. Biomolecular System Design: Architecture, Synthesis, and Simulation

    OpenAIRE

    Chiang , Katherine

    2015-01-01

    The advancements in systems and synthetic biology have been broadening the range of realizable systems with increasing complexity both in vitro and in vivo. Systems for digital logic operations, signal processing, analog computation, program flow control, as well as those composed of different functions – for example an on-site diagnostic system based on multiple biomarker measurements and signal processing – have been realized successfully. However, the efforts to date tend to tackle each de...

  9. Application of biomolecular recognition via magnetic nanoparticle in nanobiotechnology

    Science.gov (United States)

    Shen, Wei-Zheng; Cetinel, Sibel; Montemagno, Carlo

    2018-05-01

    The marriage of biomolecular recognition and magnetic nanoparticle creates tremendous opportunities in the development of advanced technology both in academic research and in industrial sectors. In this paper, we review current progress on the magnetic nanoparticle-biomolecule hybrid systems, particularly employing the recognition pairs of DNA-DNA, DNA-protein, protein-protein, and protein-inorganics in several nanobiotechnology application areas, including molecular biology, diagnostics, medical treatment, industrial biocatalysts, and environmental separations.

  10. H∞ Filtering for Networked Markovian Jump Systems with Multiple Stochastic Communication Delays

    Directory of Open Access Journals (Sweden)

    Hui Dong

    2015-01-01

    Full Text Available This paper is concerned with the H∞ filtering for a class of networked Markovian jump systems with multiple communication delays. Due to the existence of communication constraints, the measurement signal cannot arrive at the filter completely on time, and the stochastic communication delays are considered in the filter design. Firstly, a set of stochastic variables is introduced to model the occurrence probabilities of the delays. Then based on the stochastic system approach, a sufficient condition is obtained such that the filtering error system is stable in the mean-square sense and with a prescribed H∞ disturbance attenuation level. The optimal filter gain parameters can be determined by solving a convex optimization problem. Finally, a simulation example is given to show the effectiveness of the proposed filter design method.

  11. Report from the European Myeloma Network on interphase FISH in multiple myeloma and related disorders

    DEFF Research Database (Denmark)

    Ross, Fiona M; Avet-Loiseau, Hervé; Ameye, Geneviève

    2012-01-01

    The European Myeloma Network has organized two workshops on fluorescence in situ hybridization in multiple myeloma. The first aimed to identify specific indications and consensus technical approaches of current practice. A second workshop followed a quality control exercise in which 21 laboratories...... analyzed diagnostic cases of purified plasma cells for recurrent abnormalities. The summary report was discussed at the EHA Myeloma Scientific Working Group Meeting 2010. During the quality control exercise, there was acceptable agreement on more than 1,000 tests. The conclusions from the exercise were...... that the primary clinical applications for FISH analysis were for newly diagnosed cases of MM or frank relapse cases. A range of technical recommendations included: 1) material should be part of the first draw of the aspirate; 2) samples should be sent at suitable times to allow for the lengthy processing...

  12. Efficient Steplike Carrier Multiplication in Percolative Networks of Epitaxially Connected PbSe Nanocrystals.

    Science.gov (United States)

    Kulkarni, Aditya; Evers, Wiel H; Tomić, Stanko; Beard, Matthew C; Vanmaekelbergh, Daniel; Siebbeles, Laurens D A

    2018-01-23

    Carrier multiplication (CM) is a process in which a single photon excites two or more electrons. CM is of interest to enhance the efficiency of a solar cell. Until now, CM in thin films and solar cells of semiconductor nanocrystals (NCs) has been found at photon energies well above the minimum required energy of twice the band gap. The high threshold of CM strongly limits the benefits for solar cell applications. We show that CM is more efficient in a percolative network of directly connected PbSe NCs. The CM threshold is at twice the band gap and increases in a steplike fashion with photon energy. A lower CM efficiency is found for a solid of weaker coupled NCs. This demonstrates that the coupling between NCs strongly affects the CM efficiency. According to device simulations, the measured CM efficiency would significantly enhance the power conversion efficiency of a solar cell.

  13. Dynamic Allocation and Efficient Distribution of Data Among Multiple Clouds Using Network Coding

    DEFF Research Database (Denmark)

    Sipos, Marton A.; Fitzek, Frank; Roetter, Daniel Enrique Lucani

    2014-01-01

    Distributed storage has attracted large interest lately from both industry and researchers as a flexible, cost-efficient, high performance, and potentially secure solution for geographically distributed data centers, edge caching or sharing storage among users. This paper studies the benefits...... of random linear network coding to exploit multiple commercially available cloud storage providers simultaneously with the possibility to constantly adapt to changing cloud performance in order to optimize data retrieval times. The main contribution of this paper is a new data distribution mechanisms...... that cleverly stores and moves data among different clouds in order to optimize performance. Furthermore, we investigate the trade-offs among storage space, reliability and data retrieval speed for our proposed scheme. By means of real-world implementation and measurements using well-known and publicly...

  14. Tracking and Recognition of Multiple Human Targets Moving in a Wireless Pyroelectric Infrared Sensor Network

    Directory of Open Access Journals (Sweden)

    Ji Xiong

    2014-04-01

    Full Text Available With characteristics of low-cost and easy deployment, the distributed wireless pyroelectric infrared sensor network has attracted extensive interest, which aims to make it an alternate infrared video sensor in thermal biometric applications for tracking and identifying human targets. In these applications, effectively processing signals collected from sensors and extracting the features of different human targets has become crucial. This paper proposes the application of empirical mode decomposition and the Hilbert-Huang transform to extract features of moving human targets both in the time domain and the frequency domain. Moreover, the support vector machine is selected as the classifier. The experimental results demonstrate that by using this method the identification rates of multiple moving human targets are around 90%.

  15. Energy efficient design for MIMO two-way AF multiple relay networks

    KAUST Repository

    Alsharoa, Ahmad M.

    2014-04-01

    This paper studies the energy efficient transmission and the power allocation problem for multiple two-way relay networks equipped with multi-input multi-output antennas where each relay employs an amplify-and-forward strategy. The goal is to minimize the total power consumption without degrading the quality of service of the terminals. In our analysis, we start by deriving closed-form expressions of the optimal powers allocated to terminals. We then employ a strong optimization tool based on the particle swarm optimization technique to find the optimal power allocated at each relay antenna. Our numerical results illustrate the performance of the proposed scheme and show that it achieves a sub-optimal solution very close to the optimal one.

  16. A New Prime Code for Synchronous Optical Code Division Multiple-Access Networks

    Directory of Open Access Journals (Sweden)

    Huda Saleh Abbas

    2018-01-01

    Full Text Available A new spreading code based on a prime code for synchronous optical code-division multiple-access networks that can be used in monitoring applications has been proposed. The new code is referred to as “extended grouped new modified prime code.” This new code has the ability to support more terminal devices than other prime codes. In addition, it patches subsequences with “0s” leading to lower power consumption. The proposed code has an improved cross-correlation resulting in enhanced BER performance. The code construction and parameters are provided. The operating performance, using incoherent on-off keying modulation and incoherent pulse position modulation systems, has been analyzed. The performance of the code was compared with other prime codes. The results demonstrate an improved performance, and a BER floor of 10−9 was achieved.

  17. Elastic tracking versus neural network tracking for very high multiplicity problems

    International Nuclear Information System (INIS)

    Harlander, M.; Gyulassy, M.

    1991-04-01

    A new Elastic Tracking (ET) algorithm is proposed for finding tracks in very high multiplicity and noisy environments. It is based on a dynamical reinterpretation and generalization of the Radon transform and is related to elastic net algorithms for geometrical optimization. ET performs an adaptive nonlinear fit to noisy data with a variable number of tracks. Its numerics is more efficient than that of the traditional Radon or Hough transform method because it avoids binning of phase space and the costly search for valid minima. Spurious local minima are avoided in ET by introducing a time-dependent effective potential. The method is shown to be very robust to noise and measurement error and extends tracking capabilities to much higher track densities than possible via local road finding or even the novel Denby-Peterson neural network tracking algorithms. 12 refs., 2 figs

  18. The heat shock protein/chaperone network and multiple stress resistance

    KAUST Repository

    Jacob, Pierre

    2016-11-15

    Crop yield has been greatly enhanced during the last century. However, most elite cultivars are adapted to temperate climates and are not well suited to more stressful conditions. In the context of climate change, stress resistance is a major concern. To overcome these difficulties, scientists may help breeders by providing genetic markers associated with stress resistance. However, multi-stress resistance cannot be obtained from the simple addition of single stress resistance traits. In the field, stresses are unpredictable and several may occur at once. Consequently, the use of single stress resistance traits is often inadequate. Although it has been historically linked with the heat stress response, the heat shock protein (HSP)/chaperone network is a major component of multiple stress responses. Among the HSP/chaperone

  19. The heat shock protein/chaperone network and multiple stress resistance

    KAUST Repository

    Jacob, Pierre; Hirt, Heribert; Bendahmane, Abdelhafid

    2016-01-01

    Crop yield has been greatly enhanced during the last century. However, most elite cultivars are adapted to temperate climates and are not well suited to more stressful conditions. In the context of climate change, stress resistance is a major concern. To overcome these difficulties, scientists may help breeders by providing genetic markers associated with stress resistance. However, multi-stress resistance cannot be obtained from the simple addition of single stress resistance traits. In the field, stresses are unpredictable and several may occur at once. Consequently, the use of single stress resistance traits is often inadequate. Although it has been historically linked with the heat stress response, the heat shock protein (HSP)/chaperone network is a major component of multiple stress responses. Among the HSP/chaperone

  20. Stability and bifurcation in a simplified four-neuron BAM neural network with multiple delays

    Directory of Open Access Journals (Sweden)

    2006-01-01

    Full Text Available We first study the distribution of the zeros of a fourth-degree exponential polynomial. Then we apply the obtained results to a simplified bidirectional associated memory (BAM neural network with four neurons and multiple time delays. By taking the sum of the delays as the bifurcation parameter, it is shown that under certain assumptions the steady state is absolutely stable. Under another set of conditions, there are some critical values of the delay, when the delay crosses these critical values, the Hopf bifurcation occurs. Furthermore, some explicit formulae determining the stability and the direction of periodic solutions bifurcating from Hopf bifurcations are obtained by applying the normal form theory and center manifold reduction. Numerical simulations supporting the theoretical analysis are also included.

  1. Global robust stability of neural networks with multiple discrete delays and distributed delays

    International Nuclear Information System (INIS)

    Gao Ming; Cui Baotong

    2009-01-01

    The problem of global robust stability is investigated for a class of uncertain neural networks with both multiple discrete time-varying delays and distributed time-varying delays. The uncertainties are assumed to be of norm-bounded form and the activation functions are supposed to be bounded and globally Lipschitz continuous. Based on the Lyapunov stability theory and linear matrix inequality technique, some robust stability conditions guaranteeing the global robust convergence of the equilibrium point are derived. The proposed LMI-based criteria are computationally efficient as they can be easily checked by using recently developed algorithms in solving LMIs. Two examples are given to show the effectiveness of the proposed results.

  2. Coordination of networked systems on digraphs with multiple leaders via pinning control

    Science.gov (United States)

    Chen, Gang; Lewis, Frank L.

    2012-02-01

    It is well known that achieving consensus among a group of multi-vehicle systems by local distributed control is feasible if and only if all nodes in the communication digraph are reachable from a single (root) node. In this article, we take into account a more general case that the communication digraph of the networked multi-vehicle systems is weakly connected and has two or more zero-in-degree and strongly connected subgraphs, i.e. there are two or more leader groups. Based on the pinning control strategy, the feasibility problem of achieving second-order controlled consensus is studied. At first, a necessary and sufficient condition is given when the topology is fixed. Then the method to design the controller and the rule to choose the pinned vehicles are discussed. The proposed approach allows us to extend several existing results for undirected graphs to directed balanced graphs. A sufficient condition is proposed in the case where the coupling topology is variable. As an illustrative example, a second-order controlled consensus scheme is applied to coordinate the movement of networked multiple mobile robots.

  3. Tracking Control Based on Recurrent Neural Networks for Nonlinear Systems with Multiple Inputs and Unknown Deadzone

    Directory of Open Access Journals (Sweden)

    J. Humberto Pérez-Cruz

    2012-01-01

    Full Text Available This paper deals with the problem of trajectory tracking for a broad class of uncertain nonlinear systems with multiple inputs each one subject to an unknown symmetric deadzone. On the basis of a model of the deadzone as a combination of a linear term and a disturbance-like term, a continuous-time recurrent neural network is directly employed in order to identify the uncertain dynamics. By using a Lyapunov analysis, the exponential convergence of the identification error to a bounded zone is demonstrated. Subsequently, by a proper control law, the state of the neural network is compelled to follow a bounded reference trajectory. This control law is designed in such a way that the singularity problem is conveniently avoided and the exponential convergence to a bounded zone of the difference between the state of the neural identifier and the reference trajectory can be proven. Thus, the exponential convergence of the tracking error to a bounded zone and the boundedness of all closed-loop signals can be guaranteed. One of the main advantages of the proposed strategy is that the controller can work satisfactorily without any specific knowledge of an upper bound for the unmodeled dynamics and/or the disturbance term.

  4. FODA: a novel efficient multiple access protocol for highly dynamic self-organizing networks

    Science.gov (United States)

    Li, Hantao; Liu, Kai; Zhang, Jun

    2005-11-01

    Based on the concept of contention reservation for polling transmission and collision prevention strategy for collision resolution, a fair on-demand access (FODA) protocol for supporting node mobility and multihop architecture in highly dynamic self-organizing networks is proposed. In the protocol, a distributed clustering network architecture formed by self-organizing algorithm and a main idea of reserving channel resources to get polling service are adopted, so that the hidden terminal (HT) and exposed terminal (ET) problems existed in traffic transmission due to multihop architecture and wireless transmission can be eliminated completely. In addition, an improved collision prevention scheme based on binary countdown algorithm (BCA), called fair collision prevention (FCP) algorithm, is proposed to greatly eliminate unfair phenomena existed in contention access of newly active ordinary nodes and completely resolve access collisions. Finally, the performance comparison of the FODA protocol with carrier sense multiple access with collision avoidance (CSMA/CA) and polling protocols by OPNET simulation are presented. Simulation results show that the FODA protocol can overcome the disadvantages of CSMA/CA and polling protocols, and achieve higher throughput, lower average message delay and less average message dropping rate.

  5. Optimal multiple-information integration inherent in a ring neural network

    International Nuclear Information System (INIS)

    Takiyama, Ken

    2017-01-01

    Although several behavioral experiments have suggested that our neural system integrates multiple sources of information based on the certainty of each type of information in the manner of maximum-likelihood estimation, it is unclear how the maximum-likelihood estimation is implemented in our neural system. Here, I investigate the relationship between maximum-likelihood estimation and a widely used ring-type neural network model that is used as a model of visual, motor, or prefrontal cortices. Without any approximation or ansatz, I analytically demonstrate that the equilibrium of an order parameter in the neural network model exactly corresponds to the maximum-likelihood estimation when the strength of the symmetrical recurrent synaptic connectivity within a neural population is appropriately stronger than that of asymmetrical connectivity, that of local and external inputs, and that of symmetrical or asymmetrical connectivity between different neural populations. In this case, strengths of local and external inputs or those of symmetrical connectivity between different neural populations exactly correspond to the input certainty in maximum-likelihood estimation. Thus, my analysis suggests appropriately strong symmetrical recurrent connectivity as a possible candidate for implementing the maximum-likelihood estimation within our neural system. (paper)

  6. Brain Interaction during Cooperation: Evaluating Local Properties of Multiple-Brain Network.

    Science.gov (United States)

    Sciaraffa, Nicolina; Borghini, Gianluca; Aricò, Pietro; Di Flumeri, Gianluca; Colosimo, Alfredo; Bezerianos, Anastasios; Thakor, Nitish V; Babiloni, Fabio

    2017-07-21

    Subjects' interaction is the core of most human activities. This is the reason why a lack of coordination is often the cause of missing goals, more than individual failure. While there are different subjective and objective measures to assess the level of mental effort required by subjects while facing a situation that is getting harder, that is, mental workload, to define an objective measure based on how and if team members are interacting is not so straightforward. In this study, behavioral, subjective and synchronized electroencephalographic data were collected from couples involved in a cooperative task to describe the relationship between task difficulty and team coordination, in the sense of interaction aimed at cooperatively performing the assignment. Multiple-brain connectivity analysis provided information about the whole interacting system. The results showed that averaged local properties of a brain network were affected by task difficulty. In particular, strength changed significantly with task difficulty and clustering coefficients strongly correlated with the workload itself. In particular, a higher workload corresponded to lower clustering values over the central and parietal brain areas. Such results has been interpreted as less efficient organization of the network when the subjects' activities, due to high workload tendencies, were less coordinated.

  7. Multi-Destination Cognitive Radio Relay Network with SWIPT and Multiple Primary Receivers

    KAUST Repository

    Al-Habob, Ahmed A.

    2017-05-12

    In this paper, we study the performance of simultaneous wireless information and power transfer (SWIPT) technique in a multi-destination dual-hop underlay cognitive relay network with multiple primary receivers. Information transmission from the secondary source to destinations is performed entirely via a decode- and-forward (DF) relay. The relay is assumed to have no embedded power source and to harvest energy from the source signal using a power splitting (PS) protocol and employing opportunistic scheduling to forward the information to the selected destination. We derive analytical expressions for the outage probability assuming Rayleigh fading channels and considering the energy harvesting efficiency at relay, the source maximum transmit power and primary receivers interference constraints. The system performance is also studied at high signal-to-noise ratio (SNR) values where approximate expressions for the outage probability are provided and analyzed in terms of diversity order and coding gain. Monte-Carlo simulations and some numerical examples are provided to validate the derived expressions and to illustrate the effect of various system parameters on the system performance. In contrast to their conventional counterparts where a multi- destination diversity is usually achieved, the results show that the multi-destination cognitive radio relay networks with the SWIPT technique achieve a constant diversity order of one.

  8. Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks.

    Science.gov (United States)

    Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

    2016-07-14

    Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle's position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.

  9. Bayesian state space models for dynamic genetic network construction across multiple tissues.

    Science.gov (United States)

    Liang, Yulan; Kelemen, Arpad

    2016-08-01

    Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes.

  10. Interaction of multiple networks modulated by the working memory training based on real-time fMRI

    Science.gov (United States)

    Shen, Jiahui; Zhang, Gaoyan; Zhu, Chaozhe; Yao, Li; Zhao, Xiaojie

    2015-03-01

    Neuroimaging studies of working memory training have identified the alteration of brain activity as well as the regional interactions within the functional networks such as central executive network (CEN) and default mode network (DMN). However, how the interaction within and between these multiple networks is modulated by the training remains unclear. In this paper, we examined the interaction of three training-induced brain networks during working memory training based on real-time functional magnetic resonance imaging (rtfMRI). Thirty subjects assigned to the experimental and control group respectively participated in two times training separated by seven days. Three networks including silence network (SN), CEN and DMN were identified by the training data with the calculated function connections within each network. Structural equation modeling (SEM) approach was used to construct the directional connectivity patterns. The results showed that the causal influences from the percent signal changes of target ROI to the SN were positively changed in both two groups, as well as the causal influence from the SN to CEN was positively changed in experimental group but negatively changed in control group from the SN to DMN. Further correlation analysis of the changes in each network with the behavioral improvements showed that the changes in SN were stronger positively correlated with the behavioral improvement of letter memory task. These findings indicated that the SN was not only a switch between the target ROI and the other networks in the feedback training but also an essential factor to the behavioral improvement.

  11. Association between resting-state brain network topological organization and creative ability: Evidence from a multiple linear regression model.

    Science.gov (United States)

    Jiao, Bingqing; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Li, Junchao; Cai, Yuxuan; Gao, Mengxia; Gao, Zhenni; Chang, Song; Huang, Ruiwang; Liu, Ming

    2017-10-01

    Previous studies have indicated a tight linkage between resting-state functional connectivity of the human brain and creative ability. This study aimed to further investigate the association between the topological organization of resting-state brain networks and creativity. Therefore, we acquired resting-state fMRI data from 22 high-creativity participants and 22 low-creativity participants (as determined by their Torrance Tests of Creative Thinking scores). We then constructed functional brain networks for each participant and assessed group differences in network topological properties before exploring the relationships between respective network topological properties and creative ability. We identified an optimized organization of intrinsic brain networks in both groups. However, compared with low-creativity participants, high-creativity participants exhibited increased global efficiency and substantially decreased path length, suggesting increased efficiency of information transmission across brain networks in creative individuals. Using a multiple linear regression model, we further demonstrated that regional functional integration properties (i.e., the betweenness centrality and global efficiency) of brain networks, particularly the default mode network (DMN) and sensorimotor network (SMN), significantly predicted the individual differences in creative ability. Furthermore, the associations between network regional properties and creative performance were creativity-level dependent, where the difference in the resource control component may be important in explaining individual difference in creative performance. These findings provide novel insights into the neural substrate of creativity and may facilitate objective identification of creative ability. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Optimal planning of multiple distributed generation sources in distribution networks: A new approach

    Energy Technology Data Exchange (ETDEWEB)

    AlRashidi, M.R., E-mail: malrash2002@yahoo.com [Department of Electrical Engineering, College of Technological Studies, Public Authority for Applied Education and Training (PAAET) (Kuwait); AlHajri, M.F., E-mail: mfalhajri@yahoo.com [Department of Electrical Engineering, College of Technological Studies, Public Authority for Applied Education and Training (PAAET) (Kuwait)

    2011-10-15

    Highlights: {yields} A new hybrid PSO for optimal DGs placement and sizing. {yields} Statistical analysis to fine tune PSO parameters. {yields} Novel constraint handling mechanism to handle different constraints types. - Abstract: An improved particle swarm optimization algorithm (PSO) is presented for optimal planning of multiple distributed generation sources (DG). This problem can be divided into two sub-problems: the DG optimal size (continuous optimization) and location (discrete optimization) to minimize real power losses. The proposed approach addresses the two sub-problems simultaneously using an enhanced PSO algorithm capable of handling multiple DG planning in a single run. A design of experiment is used to fine tune the proposed approach via proper analysis of PSO parameters interaction. The proposed algorithm treats the problem constraints differently by adopting a radial power flow algorithm to satisfy the equality constraints, i.e. power flows in distribution networks, while the inequality constraints are handled by making use of some of the PSO features. The proposed algorithm was tested on the practical 69-bus power distribution system. Different test cases were considered to validate the proposed approach consistency in detecting optimal or near optimal solution. Results are compared with those of Sequential Quadratic Programming.

  13. Optimal planning of multiple distributed generation sources in distribution networks: A new approach

    International Nuclear Information System (INIS)

    AlRashidi, M.R.; AlHajri, M.F.

    2011-01-01

    Highlights: → A new hybrid PSO for optimal DGs placement and sizing. → Statistical analysis to fine tune PSO parameters. → Novel constraint handling mechanism to handle different constraints types. - Abstract: An improved particle swarm optimization algorithm (PSO) is presented for optimal planning of multiple distributed generation sources (DG). This problem can be divided into two sub-problems: the DG optimal size (continuous optimization) and location (discrete optimization) to minimize real power losses. The proposed approach addresses the two sub-problems simultaneously using an enhanced PSO algorithm capable of handling multiple DG planning in a single run. A design of experiment is used to fine tune the proposed approach via proper analysis of PSO parameters interaction. The proposed algorithm treats the problem constraints differently by adopting a radial power flow algorithm to satisfy the equality constraints, i.e. power flows in distribution networks, while the inequality constraints are handled by making use of some of the PSO features. The proposed algorithm was tested on the practical 69-bus power distribution system. Different test cases were considered to validate the proposed approach consistency in detecting optimal or near optimal solution. Results are compared with those of Sequential Quadratic Programming.

  14. Quantitative differentiation of multiple virus in blood using nanoporous silicon oxide immunosensor and artificial neural network.

    Science.gov (United States)

    Chakraborty, W; Ray, R; Samanta, N; RoyChaudhuri, C

    2017-12-15

    In spite of the rapid developments in various nanosensor technologies, it still remains challenging to realize a reliable ultrasensitive electrical biosensing platform which will be able to detect multiple viruses in blood simultaneously with a fairly high reproducibility without using secondary labels. In this paper, we have reported quantitative differentiation of Hep-B and Hep-C viruses in blood using nanoporous silicon oxide immunosensor array and artificial neural network (ANN). The peak frequency output (f p ) from the steady state sensitivity characteristics and the first cut off frequency (f c ) from the transient characteristics have been considered as inputs to the multilayer ANN. Implementation of several classifier blocks in the ANN architecture and coupling them with both the sensor chips, functionalized with Hep-B and Hep-C antibodies have enabled the quantification of the viruses with an accuracy of around 95% in the range of 0.04fM-1pM and with an accuracy of around 90% beyond 1pM and within 25nM in blood serum. This is the most sensitive report on multiple virus quantification using label free method. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Optical coherence tomography angiography retinal vascular network assessment in multiple sclerosis.

    Science.gov (United States)

    Lanzillo, Roberta; Cennamo, Gilda; Criscuolo, Chiara; Carotenuto, Antonio; Velotti, Nunzio; Sparnelli, Federica; Cianflone, Alessandra; Moccia, Marcello; Brescia Morra, Vincenzo

    2017-09-01

    Optical coherence tomography (OCT) angiography is a new method to assess the density of the vascular networks. Vascular abnormalities are considered involved in multiple sclerosis (MS) pathology. To assess the presence of vascular abnormalities in MS and to evaluate their correlation to disease features. A total of 50 MS patients with and without history of optic neuritis (ON) and 46 healthy subjects were included. All underwent spectral domain (SD)-OCT and OCT angiography. Clinical history, Expanded Disability Status Scale (EDSS), Multiple Sclerosis Severity Score (MSSS) and disease duration were collected. Angio-OCT showed a vessel density reduction in eyes of MS patients when compared to controls. A statistically significant reduction in all SD-OCT and OCT angiography parameters was noticed both in eyes with and without ON when compared with control eyes. We found an inverse correlation between SD-OCT parameters and MSSS ( p = 0.003) and between vessel density parameters and EDSS ( p = 0.007). We report a vessel density reduction in retina of MS patients. We highlight the clinical correlation between vessel density and EDSS, suggesting that angio-OCT could be a good marker of disease and of disability in MS.

  16. Daily Suspended Sediment Discharge Prediction Using Multiple Linear Regression and Artificial Neural Network

    Science.gov (United States)

    Uca; Toriman, Ekhwan; Jaafar, Othman; Maru, Rosmini; Arfan, Amal; Saleh Ahmar, Ansari

    2018-01-01

    Prediction of suspended sediment discharge in a catchments area is very important because it can be used to evaluation the erosion hazard, management of its water resources, water quality, hydrology project management (dams, reservoirs, and irrigation) and to determine the extent of the damage that occurred in the catchments. Multiple Linear Regression analysis and artificial neural network can be used to predict the amount of daily suspended sediment discharge. Regression analysis using the least square method, whereas artificial neural networks using Radial Basis Function (RBF) and feedforward multilayer perceptron with three learning algorithms namely Levenberg-Marquardt (LM), Scaled Conjugate Descent (SCD) and Broyden-Fletcher-Goldfarb-Shanno Quasi-Newton (BFGS). The number neuron of hidden layer is three to sixteen, while in output layer only one neuron because only one output target. The mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2 ) and coefficient of efficiency (CE) of the multiple linear regression (MLRg) value Model 2 (6 input variable independent) has the lowest the value of MAE and RMSE (0.0000002 and 13.6039) and highest R2 and CE (0.9971 and 0.9971). When compared between LM, SCG and RBF, the BFGS model structure 3-7-1 is the better and more accurate to prediction suspended sediment discharge in Jenderam catchment. The performance value in testing process, MAE and RMSE (13.5769 and 17.9011) is smallest, meanwhile R2 and CE (0.9999 and 0.9998) is the highest if it compared with the another BFGS Quasi-Newton model (6-3-1, 9-10-1 and 12-12-1). Based on the performance statistics value, MLRg, LM, SCG, BFGS and RBF suitable and accurately for prediction by modeling the non-linear complex behavior of suspended sediment responses to rainfall, water depth and discharge. The comparison between artificial neural network (ANN) and MLRg, the MLRg Model 2 accurately for to prediction suspended sediment discharge (kg

  17. Adaptive Code Division Multiple Access Protocol for Wireless Network-on-Chip Architectures

    Science.gov (United States)

    Vijayakumaran, Vineeth

    Massive levels of integration following Moore's Law ushered in a paradigm shift in the way on-chip interconnections were designed. With higher and higher number of cores on the same die traditional bus based interconnections are no longer a scalable communication infrastructure. On-chip networks were proposed enabled a scalable plug-and-play mechanism for interconnecting hundreds of cores on the same chip. Wired interconnects between the cores in a traditional Network-on-Chip (NoC) system, becomes a bottleneck with increase in the number of cores thereby increasing the latency and energy to transmit signals over them. Hence, there has been many alternative emerging interconnect technologies proposed, namely, 3D, photonic and multi-band RF interconnects. Although they provide better connectivity, higher speed and higher bandwidth compared to wired interconnects; they also face challenges with heat dissipation and manufacturing difficulties. On-chip wireless interconnects is one other alternative proposed which doesn't need physical interconnection layout as data travels over the wireless medium. They are integrated into a hybrid NOC architecture consisting of both wired and wireless links, which provides higher bandwidth, lower latency, lesser area overhead and reduced energy dissipation in communication. However, as the bandwidth of the wireless channels is limited, an efficient media access control (MAC) scheme is required to enhance the utilization of the available bandwidth. This thesis proposes using a multiple access mechanism such as Code Division Multiple Access (CDMA) to enable multiple transmitter-receiver pairs to send data over the wireless channel simultaneously. It will be shown that such a hybrid wireless NoC with an efficient CDMA based MAC protocol can significantly increase the performance of the system while lowering the energy dissipation in data transfer. In this work it is shown that the wireless NoC with the proposed CDMA based MAC protocol

  18. A replica exchange transition interface sampling method with multiple interface sets for investigating networks of rare events

    Science.gov (United States)

    Swenson, David W. H.; Bolhuis, Peter G.

    2014-07-01

    The multiple state transition interface sampling (TIS) framework in principle allows the simulation of a large network of complex rare event transitions, but in practice suffers from convergence problems. To improve convergence, we combine multiple state TIS [J. Rogal and P. G. Bolhuis, J. Chem. Phys. 129, 224107 (2008)] with replica exchange TIS [T. S. van Erp, Phys. Rev. Lett. 98, 268301 (2007)]. In addition, we introduce multiple interface sets, which allow more than one order parameter to be defined for each state. We illustrate the methodology on a model system of multiple independent dimers, each with two states. For reaction networks with up to 64 microstates, we determine the kinetics in the microcanonical ensemble, and discuss the convergence properties of the sampling scheme. For this model, we find that the kinetics depend on the instantaneous composition of the system. We explain this dependence in terms of the system's potential and kinetic energy.

  19. Scanning probe and optical tweezer investigations of biomolecular interactions

    International Nuclear Information System (INIS)

    Rigby-Singleton, Shellie

    2002-01-01

    A complex array of intermolecular forces controls the interactions between and within biological molecules. The desire to empirically explore the fundamental forces has led to the development of several biophysical techniques. Of these, the atomic force microscope (AFM) and the optical tweezers have been employed throughout this thesis to monitor the intermolecular forces involved in biomolecular interactions. The AFM is a well-established force sensing technique capable of measuring biomolecular interactions at a single molecule level. However, its versatility has not been extrapolated to the investigation of a drug-enzyme complex. The energy landscape for the force induced dissociation of the DHFR-methotrexate complex was studied. Revealing an energy barrier to dissociation located ∼0.3 nm from the bound state. Unfortunately, the AFM has a limited range of accessible loading rates and in order to profile the complete energy landscape alternative force sensing instrumentation should be considered, for example the BFP and optical tweezers. Thus, this thesis outlines the development and construction an optical trap capable of measuring intermolecular forces between biomolecules at the single molecule level. To demonstrate the force sensing abilities of the optical set up, proof of principle measurements were performed which investigate the interactions between proteins and polymer surfaces subjected to varying degrees of argon plasma treatment. Complementary data was gained from measurements performed independently by the AFM. Changes in polymer resistance to proteins as a response to changes in polymer surface chemistry were detected utilising both AFM and optical tweezers measurements. Finally, the AFM and optical tweezers were employed as ultrasensitive biosensors. Single molecule investigations of the antibody-antigen interaction between the cardiac troponin I marker and its complementary antibody, reveals the impact therapeutic concentrations of heparin have

  20. Multiple Linear Regression for Reconstruction of Gene Regulatory Networks in Solving Cascade Error Problems

    Directory of Open Access Journals (Sweden)

    Faridah Hani Mohamed Salleh

    2017-01-01

    Full Text Available Gene regulatory network (GRN reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C as a direct interaction (A → C. Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5.

  1. Yeast ribonuclease III uses a network of multiple hydrogen bonds for RNA binding and cleavage.

    Science.gov (United States)

    Lavoie, Mathieu; Abou Elela, Sherif

    2008-08-19

    Members of the bacterial RNase III family recognize a variety of short structured RNAs with few common features. It is not clear how this group of enzymes supports high cleavage fidelity while maintaining a broad base of substrates. Here we show that the yeast orthologue of RNase III (Rnt1p) uses a network of 2'-OH-dependent interactions to recognize substrates with different structures. We designed a series of bipartite substrates permitting the distinction between binding and cleavage defects. Each substrate was engineered to carry a single or multiple 2'- O-methyl or 2'-fluoro ribonucleotide substitutions to prevent the formation of hydrogen bonds with a specific nucleotide or group of nucleotides. Interestingly, introduction of 2'- O-methyl ribonucleotides near the cleavage site increased the rate of catalysis, indicating that 2'-OH are not required for cleavage. Substitution of nucleotides in known Rnt1p binding site with 2'- O-methyl ribonucleotides inhibited cleavage while single 2'-fluoro ribonucleotide substitutions did not. This indicates that while no single 2'-OH is essential for Rnt1p cleavage, small changes in the substrate structure are not tolerated. Strikingly, several nucleotide substitutions greatly increased the substrate dissociation constant with little or no effect on the Michaelis-Menten constant or rate of catalysis. Together, the results indicate that Rnt1p uses a network of nucleotide interactions to identify its substrate and support two distinct modes of binding. One mode is primarily mediated by the dsRNA binding domain and leads to the formation of stable RNA/protein complex, while the other requires the presence of the nuclease and N-terminal domains and leads to RNA cleavage.

  2. Multiple Linear Regression for Reconstruction of Gene Regulatory Networks in Solving Cascade Error Problems.

    Science.gov (United States)

    Salleh, Faridah Hani Mohamed; Zainudin, Suhaila; Arif, Shereena M

    2017-01-01

    Gene regulatory network (GRN) reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR) to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C) as a direct interaction (A → C). Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5.

  3. Vibration control of uncertain multiple launch rocket system using radial basis function neural network

    Science.gov (United States)

    Li, Bo; Rui, Xiaoting

    2018-01-01

    Poor dispersion characteristics of rockets due to the vibration of Multiple Launch Rocket System (MLRS) have always restricted the MLRS development for several decades. Vibration control is a key technique to improve the dispersion characteristics of rockets. For a mechanical system such as MLRS, the major difficulty in designing an appropriate control strategy that can achieve the desired vibration control performance is to guarantee the robustness and stability of the control system under the occurrence of uncertainties and nonlinearities. To approach this problem, a computed torque controller integrated with a radial basis function neural network is proposed to achieve the high-precision vibration control for MLRS. In this paper, the vibration response of a computed torque controlled MLRS is described. The azimuth and elevation mechanisms of the MLRS are driven by permanent magnet synchronous motors and supposed to be rigid. First, the dynamic model of motor-mechanism coupling system is established using Lagrange method and field-oriented control theory. Then, in order to deal with the nonlinearities, a computed torque controller is designed to control the vibration of the MLRS when it is firing a salvo of rockets. Furthermore, to compensate for the lumped uncertainty due to parametric variations and un-modeled dynamics in the design of the computed torque controller, a radial basis function neural network estimator is developed to adapt the uncertainty based on Lyapunov stability theory. Finally, the simulated results demonstrate the effectiveness of the proposed control system and show that the proposed controller is robust with regard to the uncertainty.

  4. Ultrafast all-optical code-division multiple-access networks

    Science.gov (United States)

    Kwong, Wing C.; Prucnal, Paul R.; Liu, Yanming

    1992-12-01

    In optical code-division multiple access (CDMA), the architecture of optical encoders/decoders is another important factor that needs to be considered, besides the correlation properties of those already extensively studied optical codes. The architecture of optical encoders/decoders affects, for example, the amount of power loss and length of optical delays that are associated with code sequence generation and correlation, which, in turn, affect the power budget, size, and cost of an optical CDMA system. Various CDMA coding architectures are studied in the paper. In contrast to the encoders/decoders used in prime networks (i.e., prime encodes/decoders), which generate, select, and correlate code sequences by a parallel combination of fiber-optic delay-lines, and in 2n networks (i.e., 2n encoders/decoders), which generate and correlate code sequences by a serial combination of 2 X 2 passive couplers and fiber delays with sequence selection performed in a parallel fashion, the modified 2n encoders/decoders generate, select, and correlate code sequences by a serial combination of directional couplers and delays. The power and delay- length requirements of the modified 2n encoders/decoders are compared to that of the prime and 2n encoders/decoders. A 100 Mbit/s optical CDMA experiment in free space demonstrating the feasibility of the all-serial coding architecture using a serial combination of 50/50 beam splitters and retroreflectors at 10 Tchip/s (i.e., 100,000 chip/bit) with 100 fs laser pulses is reported.

  5. Synergy of Two Highly Specific Biomolecular Recognition Events

    DEFF Research Database (Denmark)

    Ejlersen, Maria; Christensen, Niels Johan; Sørensen, Kasper K

    2018-01-01

    Two highly specific biomolecular recognition events, nucleic acid duplex hybridization and DNA-peptide recognition in the minor groove, were coalesced in a miniature ensemble for the first time by covalently attaching a natural AT-hook peptide motif to nucleic acid duplexes via a 2'-amino......-LNA scaffold. A combination of molecular dynamics simulations and ultraviolet thermal denaturation studies revealed high sequence-specific affinity of the peptide-oligonucleotide conjugates (POCs) when binding to complementary DNA strands, leveraging the bioinformation encrypted in the minor groove of DNA...

  6. Instrumental biosensors: new perspectives for the analysis of biomolecular interactions.

    Science.gov (United States)

    Nice, E C; Catimel, B

    1999-04-01

    The use of instrumental biosensors in basic research to measure biomolecular interactions in real time is increasing exponentially. Applications include protein-protein, protein-peptide, DNA-protein, DNA-DNA, and lipid-protein interactions. Such techniques have been applied to, for example, antibody-antigen, receptor-ligand, signal transduction, and nuclear receptor studies. This review outlines the principles of two of the most commonly used instruments and highlights specific operating parameters that will assist in optimising experimental design, data generation, and analysis.

  7. Application of Hidden Markov Models in Biomolecular Simulations.

    Science.gov (United States)

    Shukla, Saurabh; Shamsi, Zahra; Moffett, Alexander S; Selvam, Balaji; Shukla, Diwakar

    2017-01-01

    Hidden Markov models (HMMs) provide a framework to analyze large trajectories of biomolecular simulation datasets. HMMs decompose the conformational space of a biological molecule into finite number of states that interconvert among each other with certain rates. HMMs simplify long timescale trajectories for human comprehension, and allow comparison of simulations with experimental data. In this chapter, we provide an overview of building HMMs for analyzing bimolecular simulation datasets. We demonstrate the procedure for building a Hidden Markov model for Met-enkephalin peptide simulation dataset and compare the timescales of the process.

  8. An Interference-Aware Traffic-Priority-Based Link Scheduling Algorithm for Interference Mitigation in Multiple Wireless Body Area Networks

    Directory of Open Access Journals (Sweden)

    Thien T. T. Le

    2016-12-01

    Full Text Available Currently, wireless body area networks (WBANs are effectively used for health monitoring services. However, in cases where WBANs are densely deployed, interference among WBANs can cause serious degradation of network performance and reliability. Inter-WBAN interference can be reduced by scheduling the communication links of interfering WBANs. In this paper, we propose an interference-aware traffic-priority-based link scheduling (ITLS algorithm to overcome inter-WBAN interference in densely deployed WBANs. First, we model a network with multiple WBANs as an interference graph where node-level interference and traffic priority are taken into account. Second, we formulate link scheduling for multiple WBANs as an optimization model where the objective is to maximize the throughput of the entire network while ensuring the traffic priority of sensor nodes. Finally, we propose the ITLS algorithm for multiple WBANs on the basis of the optimization model. High spatial reuse is also achieved in the proposed ITLS algorithm. The proposed ITLS achieves high spatial reuse while considering traffic priority, packet length, and the number of interfered sensor nodes. Our simulation results show that the proposed ITLS significantly increases spatial reuse and network throughput with lower delay by mitigating inter-WBAN interference.

  9. Phylogeny and evolutionary histories of Pyrus L. revealed by phylogenetic trees and networks based on data from multiple DNA sequences

    Science.gov (United States)

    Reconstructing the phylogeny of Pyrus has been difficult due to the wide distribution of the genus and lack of informative data. In this study, we collected 110 accessions representing 25 Pyrus species and constructed both phylogenetic trees and phylogenetic networks based on multiple DNA sequence d...

  10. Nonorthogonal multiple access and carrierless amplitude phase modulation for flexible multiuser provisioning in 5G mobile networks

    NARCIS (Netherlands)

    Altabas, J.A.; Rommel, S.; Puerta, R.; Izquierdo, D.; Ignacio Garces, J.; Antonio Lazaro, J.; Vegas Olmos, J.J.; Tafur Monroy, I.

    2017-01-01

    In this paper, a combined nonorthogonal multiple access (NOMA) and multiband carrierless amplitude phase modulation (multiCAP) scheme is proposed for capacity enhancement of and flexible resource provisioning in 5G mobile networks. The proposed scheme is experimentally evaluated over a W-band

  11. KeyPathwayMiner - De-novo network enrichment by combining multiple OMICS data and biological networks

    DEFF Research Database (Denmark)

    Baumbach, Jan; Alcaraz, Nicolas; Pauling, Josch K.

    We tackle the problem of de-novo pathway extraction. Given a biological network and a set of case-control studies, KeyPathwayMiner efficiently extracts and visualizes all maximal connected sub-networks that contain mainly genes that are dysregulated, e.g., differentially expressed, in most cases ...

  12. Using Bayesian Belief Networks To Assess Volcano State from Multiple Monitoring Timeseries And Other Evidence

    Science.gov (United States)

    Odbert, Henry; Aspinall, Willy

    2013-04-01

    When volcanoes exhibit unrest or become eruptively active, science-based decision support invariably is sought by civil authorities. Evidence available to scientists about a volcano's internal state is usually indirect, secondary or very nebulous.Advancement of volcano monitoring technology in recent decades has increased the variety and resolution of multi-parameter timeseries data recorded at volcanoes. Monitoring timeseries may be interpreted in real time by observatory staff and are often later subjected to further analytic scrutiny by the research community at large. With increasing variety and resolution of data, interpreting these multiple strands of parallel, partial evidence has become increasingly complex. In practice, interpretation of many timeseries involves familiarity with the idiosyncracies of the volcano, the monitoring techniques, the configuration of the recording instrumentation, observations from other datasets, and so on. Assimilation of this knowledge is necessary in order to select and apply the appropriate statistical techniques required to extract the required information. Bayesian Belief Networks (BBNs) use probability theory to treat and evaluate uncertainties in a rational and auditable scientific manner, but only to the extent warranted by the strength of the available evidence. The concept is a suitable framework for marshalling multiple observations, model results and interpretations - and associated uncertainties - in a methodical manner. The formulation is usually implemented in graphical form and could be developed as a tool for near real-time, ongoing use in a volcano observatory, for example. We explore the application of BBNs in analysing volcanic timeseries, the certainty with which inferences may be drawn, and how they can be updated dynamically. Such approaches provide a route to developing analytical interface(s) between volcano monitoring analyses and probabilistic hazard analysis. We discuss the use of BBNs in hazard

  13. MrTADFinder: A network modularity based approach to identify topologically associating domains in multiple resolutions.

    Directory of Open Access Journals (Sweden)

    Koon-Kiu Yan

    2017-07-01

    Full Text Available Genome-wide proximity ligation based assays such as Hi-C have revealed that eukaryotic genomes are organized into structural units called topologically associating domains (TADs. From a visual examination of the chromosomal contact map, however, it is clear that the organization of the domains is not simple or obvious. Instead, TADs exhibit various length scales and, in many cases, a nested arrangement. Here, by exploiting the resemblance between TADs in a chromosomal contact map and densely connected modules in a network, we formulate TAD identification as a network optimization problem and propose an algorithm, MrTADFinder, to identify TADs from intra-chromosomal contact maps. MrTADFinder is based on the network-science concept of modularity. A key component of it is deriving an appropriate background model for contacts in a random chain, by numerically solving a set of matrix equations. The background model preserves the observed coverage of each genomic bin as well as the distance dependence of the contact frequency for any pair of bins exhibited by the empirical map. Also, by introducing a tunable resolution parameter, MrTADFinder provides a self-consistent approach for identifying TADs at different length scales, hence the acronym "Mr" standing for Multiple Resolutions. We then apply MrTADFinder to various Hi-C datasets. The identified domain boundaries are marked by characteristic signatures in chromatin marks and transcription factors (TF that are consistent with earlier work. Moreover, by calling TADs at different length scales, we observe that boundary signatures change with resolution, with different chromatin features having different characteristic length scales. Furthermore, we report an enrichment of HOT (high-occupancy target regions near TAD boundaries and investigate the role of different TFs in determining boundaries at various resolutions. To further explore the interplay between TADs and epigenetic marks, as tumor mutational

  14. ADNP-CSMA Random Multiple Access protocol application with the function of monitoring in Ad Hoc network

    Directory of Open Access Journals (Sweden)

    Zhan Gang

    2016-01-01

    Full Text Available In Ad Hoc networks,the net work of mobile nodes exchange information with their wireless transceiver equipment,the network throughput is in increased,compared to other such multiple hops network.Moreover along with the rapid development of modern information,communication business also will be increase.However,the access and adaptive of previous CSMA protocol are insufficient.According to these properties,this paper presents a kind of adaptive dual clock with monitoring function P-CSMA random multiple access protocol(ADNP-CSMA,and discusses two kinds of P-CSMA.ACK with monitoring function is introduced to maintain the stability of the whole system,and the introduction of dual clock mechanism reduces the channel of idle period.It calculate the system throughput expression through the method of average period,and the simulation results show that the system is constant in the case of high load throughput.

  15. QSAR Study of Insecticides of Phthalamide Derivatives Using Multiple Linear Regression and Artificial Neural Network Methods

    Directory of Open Access Journals (Sweden)

    Adi Syahputra

    2014-03-01

    Full Text Available Quantitative structure activity relationship (QSAR for 21 insecticides of phthalamides containing hydrazone (PCH was studied using multiple linear regression (MLR, principle component regression (PCR and artificial neural network (ANN. Five descriptors were included in the model for MLR and ANN analysis, and five latent variables obtained from principle component analysis (PCA were used in PCR analysis. Calculation of descriptors was performed using semi-empirical PM6 method. ANN analysis was found to be superior statistical technique compared to the other methods and gave a good correlation between descriptors and activity (r2 = 0.84. Based on the obtained model, we have successfully designed some new insecticides with higher predicted activity than those of previously synthesized compounds, e.g.2-(decalinecarbamoyl-5-chloro-N’-((5-methylthiophen-2-ylmethylene benzohydrazide, 2-(decalinecarbamoyl-5-chloro-N’-((thiophen-2-yl-methylene benzohydrazide and 2-(decaline carbamoyl-N’-(4-fluorobenzylidene-5-chlorobenzohydrazide with predicted log LC50 of 1.640, 1.672, and 1.769 respectively.

  16. A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery.

    Directory of Open Access Journals (Sweden)

    Yan Liu

    Full Text Available Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS treatment planning. In this work, we developed a deep learning convolutional neural network (CNN algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image Segmentation challenge (BRATS data and clinical patients' data. Validation on BRATS data yielded average DICE coefficients (DCs of 0.75±0.07 in the tumor core and 0.81±0.04 in the enhancing tumor, which outperformed most techniques in the 2015 BRATS challenge. Segmentation results of patient cases showed an average of DCs 0.67±0.03 and achieved an area under the receiver operating characteristic curve of 0.98±0.01. The developed automatic segmentation strategy surpasses current benchmark levels and offers a promising tool for SRS treatment planning for multiple brain metastases.

  17. Multiple-Antenna Interference Cancellation for WLAN with MAC Interference Avoidance in Open Access Networks

    Directory of Open Access Journals (Sweden)

    Alexandr M. Kuzminskiy

    2007-10-01

    Full Text Available The potential of multiantenna interference cancellation receiver algorithms for increasing the uplink throughput in WLAN systems such as 802.11 is investigated. The medium access control (MAC in such systems is based on carrier sensing multiple-access with collision avoidance (CSMA/CA, which itself is a powerful tool for the mitigation of intrasystem interference. However, due to the spatial dependence of received signal strengths, it is possible for the collision avoidance mechanism to fail, resulting in packet collisions at the receiver and a reduction in system throughput. The CSMA/CA MAC protocol can be complemented in such scenarios by interference cancellation (IC algorithms at the physical (PHY layer. The corresponding gains in throughput are a result of the complex interplay between the PHY and MAC layers. It is shown that semiblind interference cancellation techniques are essential for mitigating the impact of interference bursts, in particular since these are typically asynchronous with respect to the desired signal burst. Semiblind IC algorithms based on second- and higher-order statistics are compared to the conventional no-IC and training-based IC techniques in an open access network (OAN scenario involving home and visiting users. It is found that the semiblind IC algorithms significantly outperform the other techniques due to the bursty and asynchronous nature of the interference caused by the MAC interference avoidance scheme.

  18. Multiple-Antenna Interference Cancellation for WLAN with MAC Interference Avoidance in Open Access Networks

    Directory of Open Access Journals (Sweden)

    Kuzminskiy Alexandr M

    2007-01-01

    Full Text Available The potential of multiantenna interference cancellation receiver algorithms for increasing the uplink throughput in WLAN systems such as 802.11 is investigated. The medium access control (MAC in such systems is based on carrier sensing multiple-access with collision avoidance (CSMA/CA, which itself is a powerful tool for the mitigation of intrasystem interference. However, due to the spatial dependence of received signal strengths, it is possible for the collision avoidance mechanism to fail, resulting in packet collisions at the receiver and a reduction in system throughput. The CSMA/CA MAC protocol can be complemented in such scenarios by interference cancellation (IC algorithms at the physical (PHY layer. The corresponding gains in throughput are a result of the complex interplay between the PHY and MAC layers. It is shown that semiblind interference cancellation techniques are essential for mitigating the impact of interference bursts, in particular since these are typically asynchronous with respect to the desired signal burst. Semiblind IC algorithms based on second- and higher-order statistics are compared to the conventional no-IC and training-based IC techniques in an open access network (OAN scenario involving home and visiting users. It is found that the semiblind IC algorithms significantly outperform the other techniques due to the bursty and asynchronous nature of the interference caused by the MAC interference avoidance scheme.

  19. Ear Detection under Uncontrolled Conditions with Multiple Scale Faster Region-Based Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Yi Zhang

    2017-04-01

    Full Text Available Ear detection is an important step in ear recognition approaches. Most existing ear detection techniques are based on manually designing features or shallow learning algorithms. However, researchers found that the pose variation, occlusion, and imaging conditions provide a great challenge to the traditional ear detection methods under uncontrolled conditions. This paper proposes an efficient technique involving Multiple Scale Faster Region-based Convolutional Neural Networks (Faster R-CNN to detect ears from 2D profile images in natural images automatically. Firstly, three regions of different scales are detected to infer the information about the ear location context within the image. Then an ear region filtering approach is proposed to extract the correct ear region and eliminate the false positives automatically. In an experiment with a test set of 200 web images (with variable photographic conditions, 98% of ears were accurately detected. Experiments were likewise conducted on the Collection J2 of University of Notre Dame Biometrics Database (UND-J2 and University of Beira Interior Ear dataset (UBEAR, which contain large occlusion, scale, and pose variations. Detection rates of 100% and 98.22%, respectively, demonstrate the effectiveness of the proposed approach.

  20. Mass detection in digital breast tomosynthesis data using convolutional neural networks and multiple instance learning.

    Science.gov (United States)

    Yousefi, Mina; Krzyżak, Adam; Suen, Ching Y

    2018-05-01

    Digital breast tomosynthesis (DBT) was developed in the field of breast cancer screening as a new tomographic technique to minimize the limitations of conventional digital mammography breast screening methods. A computer-aided detection (CAD) framework for mass detection in DBT has been developed and is described in this paper. The proposed framework operates on a set of two-dimensional (2D) slices. With plane-to-plane analysis on corresponding 2D slices from each DBT, it automatically learns complex patterns of 2D slices through a deep convolutional neural network (DCNN). It then applies multiple instance learning (MIL) with a randomized trees approach to classify DBT images based on extracted information from 2D slices. This CAD framework was developed and evaluated using 5040 2D image slices derived from 87 DBT volumes. The empirical results demonstrate that this proposed CAD framework achieves much better performance than CAD systems that use hand-crafted features and deep cardinality-restricted Bolzmann machines to detect masses in DBTs. Copyright © 2018 Elsevier Ltd. All rights reserved.

  1. Modern drug design: the implication of using artificial neuronal networks and multiple molecular dynamic simulations

    Science.gov (United States)

    Yakovenko, Oleksandr; Jones, Steven J. M.

    2018-01-01

    We report the implementation of molecular modeling approaches developed as a part of the 2016 Grand Challenge 2, the blinded competition of computer aided drug design technologies held by the D3R Drug Design Data Resource (https://drugdesigndata.org/). The challenge was focused on the ligands of the farnesoid X receptor (FXR), a highly flexible nuclear receptor of the cholesterol derivative chenodeoxycholic acid. FXR is considered an important therapeutic target for metabolic, inflammatory, bowel and obesity related diseases (Expert Opin Drug Metab Toxicol 4:523-532, 2015), but in the context of this competition it is also interesting due to the significant ligand-induced conformational changes displayed by the protein. To deal with these conformational changes we employed multiple simulations of molecular dynamics (MD). Our MD-based protocols were top-ranked in estimating the free energy of binding of the ligands and FXR protein. Our approach was ranked second in the prediction of the binding poses where we also combined MD with molecular docking and artificial neural networks. Our approach showed mediocre results for high-throughput scoring of interactions.

  2. Synthetic Approach to biomolecular science by cyborg supramolecular chemistry.

    Science.gov (United States)

    Kurihara, Kensuke; Matsuo, Muneyuki; Yamaguchi, Takumi; Sato, Sota

    2018-02-01

    To imitate the essence of living systems via synthetic chemistry approaches has been attempted. With the progress in supramolecular chemistry, it has become possible to synthesize molecules of a size and complexity close to those of biomacromolecules. Recently, the combination of precisely designed supramolecules with biomolecules has generated structural platforms for designing and creating unique molecular systems. Bridging between synthetic chemistry and biomolecular science is also developing methodologies for the creation of artificial cellular systems. This paper provides an overview of the recently expanding interdisciplinary research to fuse artificial molecules with biomolecules, that can deepen our understanding of the dynamical ordering of biomolecules. Using bottom-up approaches based on the precise chemical design, synthesis and hybridization of artificial molecules with biological materials have been realizing the construction of sophisticated platforms having the fundamental functions of living systems. The effective hybrid, molecular cyborg, approaches enable not only the establishment of dynamic systems mimicking nature and thus well-defined models for biophysical understanding, but also the creation of those with highly advanced, integrated functions. This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Selected topics in solution-phase biomolecular NMR spectroscopy

    Science.gov (United States)

    Kay, Lewis E.; Frydman, Lucio

    2017-05-01

    Solution bio-NMR spectroscopy continues to enjoy a preeminent role as an important tool in elucidating the structure and dynamics of a range of important biomolecules and in relating these to function. Equally impressive is how NMR continues to 'reinvent' itself through the efforts of many brilliant practitioners who ask increasingly demanding and increasingly biologically relevant questions. The ability to manipulate spin Hamiltonians - almost at will - to dissect the information of interest contributes to the success of the endeavor and ensures that the NMR technology will be well poised to contribute to as yet unknown frontiers in the future. As a tribute to the versatility of solution NMR in biomolecular studies and to the continued rapid advances in the field we present a Virtual Special Issue (VSI) that includes over 40 articles on various aspects of solution-state biomolecular NMR that have been published in the Journal of Magnetic Resonance in the past 7 years. These, in total, help celebrate the achievements of this vibrant field.

  4. Photochirogenesis: Photochemical Models on the Origin of Biomolecular Homochirality

    Directory of Open Access Journals (Sweden)

    Cornelia Meinert

    2010-05-01

    Full Text Available Current research focuses on a better understanding of the origin of biomolecular asymmetry by the identification and detection of the possibly first chiral molecules that were involved in the appearance and evolution of life on Earth. We have reasons to assume that these molecules were specific chiral amino acids. Chiral amino acids have been identified in both chondritic meteorites and simulated interstellar ices. Present research reasons that circularly polarized electromagnetic radiation was identified in interstellar environments and an asymmetric interstellar photon-molecule interaction might have triggered biomolecular symmetry breaking. We review on the possible prebiotic interaction of ‘chiral photons’ in the form of circularly polarized light, with early chiral organic molecules. We will highlight recent studies on enantioselective photolysis of racemic amino acids by circularly polarized light and experiments on the asymmetric photochemical synthesis of amino acids from only one C and one N containing molecules by simulating interstellar environments. Both approaches are based on circular dichroic transitions of amino acids that will be presented as well.

  5. An Overview of Biomolecular Event Extraction from Scientific Documents.

    Science.gov (United States)

    Vanegas, Jorge A; Matos, Sérgio; González, Fabio; Oliveira, José L

    2015-01-01

    This paper presents a review of state-of-the-art approaches to automatic extraction of biomolecular events from scientific texts. Events involving biomolecules such as genes, transcription factors, or enzymes, for example, have a central role in biological processes and functions and provide valuable information for describing physiological and pathogenesis mechanisms. Event extraction from biomedical literature has a broad range of applications, including support for information retrieval, knowledge summarization, and information extraction and discovery. However, automatic event extraction is a challenging task due to the ambiguity and diversity of natural language and higher-level linguistic phenomena, such as speculations and negations, which occur in biological texts and can lead to misunderstanding or incorrect interpretation. Many strategies have been proposed in the last decade, originating from different research areas such as natural language processing, machine learning, and statistics. This review summarizes the most representative approaches in biomolecular event extraction and presents an analysis of the current state of the art and of commonly used methods, features, and tools. Finally, current research trends and future perspectives are also discussed.

  6. An Overview of Biomolecular Event Extraction from Scientific Documents

    Directory of Open Access Journals (Sweden)

    Jorge A. Vanegas

    2015-01-01

    Full Text Available This paper presents a review of state-of-the-art approaches to automatic extraction of biomolecular events from scientific texts. Events involving biomolecules such as genes, transcription factors, or enzymes, for example, have a central role in biological processes and functions and provide valuable information for describing physiological and pathogenesis mechanisms. Event extraction from biomedical literature has a broad range of applications, including support for information retrieval, knowledge summarization, and information extraction and discovery. However, automatic event extraction is a challenging task due to the ambiguity and diversity of natural language and higher-level linguistic phenomena, such as speculations and negations, which occur in biological texts and can lead to misunderstanding or incorrect interpretation. Many strategies have been proposed in the last decade, originating from different research areas such as natural language processing, machine learning, and statistics. This review summarizes the most representative approaches in biomolecular event extraction and presents an analysis of the current state of the art and of commonly used methods, features, and tools. Finally, current research trends and future perspectives are also discussed.

  7. Ion induced fragmentation of biomolecular systems at low collision energies

    International Nuclear Information System (INIS)

    Bernigaud, V; Adoui, L; Chesnel, J Y; Rangama, J; Huber, B A; Manil, B; Alvarado, F; Bari, S; Hoekstra, R; Postma, J; Schlathoelter, T

    2009-01-01

    In this paper, we present results of different collision experiments between multiply charged ions at low collision energies (in the keV-region) and biomolecular systems. This kind of interaction allows to remove electrons form the biomolecule without transferring a large amount of vibrational excitation energy. Nevertheless, following the ionization of the target, fragmentation of biomolecular species may occur. It is the main objective of this work to study the physical processes involved in the dissociation of highly electronically excited systems. In order to elucidate the intrinsic properties of certain biomolecules (porphyrins and amino acids) we have performed experiments in the gas phase with isolated systems. The obtained results demonstrate the high stability of porphyrins after electron removal. Furthermore, a dependence of the fragmentation pattern produced by multiply charged ions on the isomeric structure of the alanine molecule has been shown. By considering the presence of other surrounding biomolecules (clusters of nucleobases), a strong influence of the environment of the biomolecule on the fragmentation channels and their modification, has been clearly proven. This result is explained, in the thymine and uracil case, by the formation of hydrogen bonds between O and H atoms, which is known to favor planar cluster geometries.

  8. MPBEC, a Matlab Program for Biomolecular Electrostatic Calculations.

    Science.gov (United States)

    Vergara-Perez, Sandra; Marucho, Marcelo

    2016-01-01

    One of the most used and efficient approaches to compute electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation. There are several software packages available that solve the PB equation for molecules in aqueous electrolyte solutions. Most of these software packages are useful for scientists with specialized training and expertise in computational biophysics. However, the user is usually required to manually take several important choices, depending on the complexity of the biological system, to successfully obtain the numerical solution of the PB equation. This may become an obstacle for researchers, experimentalists, even students with no special training in computational methodologies. Aiming to overcome this limitation, in this article we present MPBEC, a free, cross-platform, open-source software that provides non-experts in the field an easy and efficient way to perform biomolecular electrostatic calculations on single processor computers. MPBEC is a Matlab script based on the Adaptative Poisson Boltzmann Solver, one of the most popular approaches used to solve the PB equation. MPBEC does not require any user programming, text editing or extensive statistical skills, and comes with detailed user-guide documentation. As a unique feature, MPBEC includes a useful graphical user interface (GUI) application which helps and guides users to configure and setup the optimal parameters and approximations to successfully perform the required biomolecular electrostatic calculations. The GUI also incorporates visualization tools to facilitate users pre- and post- analysis of structural and electrical properties of biomolecules.

  9. MPBEC, a Matlab Program for Biomolecular Electrostatic Calculations

    Science.gov (United States)

    Vergara-Perez, Sandra; Marucho, Marcelo

    2016-01-01

    One of the most used and efficient approaches to compute electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation. There are several software packages available that solve the PB equation for molecules in aqueous electrolyte solutions. Most of these software packages are useful for scientists with specialized training and expertise in computational biophysics. However, the user is usually required to manually take several important choices, depending on the complexity of the biological system, to successfully obtain the numerical solution of the PB equation. This may become an obstacle for researchers, experimentalists, even students with no special training in computational methodologies. Aiming to overcome this limitation, in this article we present MPBEC, a free, cross-platform, open-source software that provides non-experts in the field an easy and efficient way to perform biomolecular electrostatic calculations on single processor computers. MPBEC is a Matlab script based on the Adaptative Poisson-Boltzmann Solver, one of the most popular approaches used to solve the PB equation. MPBEC does not require any user programming, text editing or extensive statistical skills, and comes with detailed user-guide documentation. As a unique feature, MPBEC includes a useful graphical user interface (GUI) application which helps and guides users to configure and setup the optimal parameters and approximations to successfully perform the required biomolecular electrostatic calculations. The GUI also incorporates visualization tools to facilitate users pre- and post-analysis of structural and electrical properties of biomolecules.

  10. Securing optical code-division multiple-access networks with a postswitching coding scheme of signature reconfiguration

    Science.gov (United States)

    Huang, Jen-Fa; Meng, Sheng-Hui; Lin, Ying-Chen

    2014-11-01

    The optical code-division multiple-access (OCDMA) technique is considered a good candidate for providing optical layer security. An enhanced OCDMA network security mechanism with a pseudonoise (PN) random digital signals type of maximal-length sequence (M-sequence) code switching to protect against eavesdropping is presented. Signature codes unique to individual OCDMA-network users are reconfigured according to the register state of the controlling electrical shift registers. Examples of signature reconfiguration following state switching of the controlling shift register for both the network user and the eavesdropper are numerically illustrated. Dynamically changing the PN state of the shift register to reconfigure the user signature sequence is shown; this hinders eavesdroppers' efforts to decode correct data sequences. The proposed scheme increases the probability of eavesdroppers committing errors in decoding and thereby substantially enhances the degree of an OCDMA network's confidentiality.

  11. Multiple brain networks underpinning word learning from fluent speech revealed by independent component analysis.

    Science.gov (United States)

    López-Barroso, Diana; Ripollés, Pablo; Marco-Pallarés, Josep; Mohammadi, Bahram; Münte, Thomas F; Bachoud-Lévi, Anne-Catherine; Rodriguez-Fornells, Antoni; de Diego-Balaguer, Ruth

    2015-04-15

    Although neuroimaging studies using standard subtraction-based analysis from functional magnetic resonance imaging (fMRI) have suggested that frontal and temporal regions are involved in word learning from fluent speech, the possible contribution of different brain networks during this type of learning is still largely unknown. Indeed, univariate fMRI analyses cannot identify the full extent of distributed networks that are engaged by a complex task such as word learning. Here we used Independent Component Analysis (ICA) to characterize the different brain networks subserving word learning from an artificial language speech stream. Results were replicated in a second cohort of participants with a different linguistic background. Four spatially independent networks were associated with the task in both cohorts: (i) a dorsal Auditory-Premotor network; (ii) a dorsal Sensory-Motor network; (iii) a dorsal Fronto-Parietal network; and (iv) a ventral Fronto-Temporal network. The level of engagement of these networks varied through the learning period with only the dorsal Auditory-Premotor network being engaged across all blocks. In addition, the connectivity strength of this network in the second block of the learning phase correlated with the individual variability in word learning performance. These findings suggest that: (i) word learning relies on segregated connectivity patterns involving dorsal and ventral networks; and (ii) specifically, the dorsal auditory-premotor network connectivity strength is directly correlated with word learning performance. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. Secure Communications in High Speed Fiber Optical Networks Using Code Division Multiple Access (CDMA) Transmission

    Energy Technology Data Exchange (ETDEWEB)

    Han, I; Bond, S; Welty, R; Du, Y; Yoo, S; Reinhardt, C; Behymer, E; Sperry, V; Kobayashi, N

    2004-02-12

    This project is focused on the development of advanced components and system technologies for secure data transmission on high-speed fiber optic data systems. This work capitalizes on (1) a strong relationship with outstanding faculty at the University of California-Davis who are experts in high speed fiber-optic networks, (2) the realization that code division multiple access (CDMA) is emerging as a bandwidth enhancing technique for fiber optic networks, (3) the realization that CDMA of sufficient complexity forms the basis for almost unbreakable one-time key transmissions, (4) our concepts for superior components for implementing CDMA, (5) our expertise in semiconductor device processing and (6) our Center for Nano and Microtechnology, which is where the majority of the experimental work was done. Here we present a novel device concept, which will push the limits of current technology, and will simultaneously solve system implementation issues by investigating new state-of-the-art fiber technologies. This will enable the development of secure communication systems for the transmission and reception of messages on deployed commercial fiber optic networks, through the CDMA phase encoding of broad bandwidth pulses. CDMA technology has been developed as a multiplexing technology, much like wavelength division multiplexing (WDM) or time division multiplexing (TDM), to increase the potential number of users on a given communication link. A novel application of the techniques created for CDMA is to generate secure communication through physical layer encoding. Physical layer encoding devices are developed which utilize semiconductor waveguides with fast carrier response times to phase encode spectral components of a secure signal. Current commercial technology, most commonly a spatial light modulator, allows phase codes to be changed at rates of only 10's of Hertz ({approx}25ms response). The use of fast (picosecond to nanosecond) carrier dynamics of semiconductors

  13. Low-cost design of next generation SONET/SDH networks with multiple constraints

    CSIR Research Space (South Africa)

    Karem, TR

    2007-07-01

    Full Text Available on constraints programming satisfaction technology is proposed. The algorithm is tested in OPNET simulation environment using different network models derived from a hypothetical case study of an optical network design for Bellville area in Cape Town, South...

  14. Tunable optical frequency comb enabled scalable and cost-effective multiuser orthogonal frequency-division multiple access passive optical network with source-free optical network units.

    Science.gov (United States)

    Chen, Chen; Zhang, Chongfu; Liu, Deming; Qiu, Kun; Liu, Shuang

    2012-10-01

    We propose and experimentally demonstrate a multiuser orthogonal frequency-division multiple access passive optical network (OFDMA-PON) with source-free optical network units (ONUs), enabled by tunable optical frequency comb generation technology. By cascading a phase modulator (PM) and an intensity modulator and dynamically controlling the peak-to-peak voltage of a PM driven signal, a tunable optical frequency comb source can be generated. It is utilized to assist the configuration of a multiple source-free ONUs enhanced OFDMA-PON where simultaneous and interference-free multiuser upstream transmission over a single wavelength can be efficiently supported. The proposed multiuser OFDMA-PON is scalable and cost effective, and its feasibility is successfully verified by experiment.

  15. Modeling and Control of Heat Networks with Storage : the Single-Producer Multiple-Consumer Case

    NARCIS (Netherlands)

    Scholten, Tjeert Wobko; De Persis, Claudio; Tesi, Pietro

    2015-01-01

    In heat networks, energy storage is a viable approach to balance demand and supply. In such a network, a heat carrier is used in the form of water, where heat is injected and extracted through heat exchangers. The network can transport and store heated water in stratification tanks to shift loads in

  16. Modeling and control of heat networks with storage: The single-producer multiple-consumer case.

    NARCIS (Netherlands)

    Scholten, Tjardo; De Persis, Claudio; Tesi, Pietro

    2015-01-01

    In heat networks, energy storage is a viable approach to balance demand and supply. In such a network, a heat carrier is used in the form of water, where heat is injected and extracted through heat exchangers. The network can transport and store heated water in stratification tanks to shift loads in

  17. Logarithmic r-θ mapping for hybrid optical neural network filter for multiple objects recognition within cluttered scenes

    Science.gov (United States)

    Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.; Birch, Phil M.

    2009-04-01

    θThe window unit in the design of the complex logarithmic r-θ mapping for hybrid optical neural network filter can allow multiple objects of the same class to be detected within the input image. Additionally, the architecture of the neural network unit of the complex logarithmic r-θ mapping for hybrid optical neural network filter becomes attractive for accommodating the recognition of multiple objects of different classes within the input image by modifying the output layer of the unit. We test the overall filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. Logarithmic r-θ mapping for hybrid optical neural network filter is shown to exhibit with a single pass over the input data simultaneously in-plane rotation, out-of-plane rotation, scale, log r-θ map translation and shift invariance, and good clutter tolerance by recognizing correctly the different objects within the cluttered scenes. We record in our results additional extracted information from the cluttered scenes about the objects' relative position, scale and in-plane rotation.

  18. Multiple Substrate Usage of Coxiella burnetii to Feed a Bipartite Metabolic Network

    Directory of Open Access Journals (Sweden)

    Ina Häuslein

    2017-06-01

    Full Text Available The human pathogen Coxiella burnetii causes Q-fever and is classified as a category B bio-weapon. Exploiting the development of the axenic growth medium ACCM-2, we have now used 13C-labeling experiments and isotopolog profiling to investigate the highly diverse metabolic network of C. burnetii. To this aim, C. burnetii RSA 439 NMII was cultured in ACCM-2 containing 5 mM of either [U-13C3]serine, [U-13C6]glucose, or [U-13C3]glycerol until the late-logarithmic phase. GC/MS-based isotopolog profiling of protein-derived amino acids, methanol-soluble polar metabolites, fatty acids, and cell wall components (e.g., diaminopimelate and sugars from the labeled bacteria revealed differential incorporation rates and isotopolog profiles. These data served to decipher the diverse usages of the labeled substrates and the relative carbon fluxes into the core metabolism of the pathogen. Whereas, de novo biosynthesis from any of these substrates could not be found for histidine, isoleucine, leucine, lysine, phenylalanine, proline and valine, the other amino acids and metabolites under study acquired 13C-label at specific rates depending on the nature of the tracer compound. Glucose was directly used for cell wall biosynthesis, but was also converted into pyruvate (and its downstream metabolites through the glycolytic pathway or into erythrose 4-phosphate (e.g., for the biosynthesis of tyrosine via the non-oxidative pentose phosphate pathway. Glycerol efficiently served as a gluconeogenetic substrate and could also be used via phosphoenolpyruvate and diaminopimelate as a major carbon source for cell wall biosynthesis. In contrast, exogenous serine was mainly utilized in downstream metabolic processes, e.g., via acetyl-CoA in a complete citrate cycle with fluxes in the oxidative direction and as a carbon feed for fatty acid biosynthesis. In summary, the data reflect multiple and differential substrate usages by C. burnetii in a bipartite-type metabolic network

  19. Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach.

    Science.gov (United States)

    Chandrasekar, A; Rakkiyappan, R; Cao, Jinde

    2015-10-01

    This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is governed by Bernoulli random variable. The aim of this paper is to obtain the synchronization criteria, which is suitable for both exactly known and partly unknown transition probabilities such that the coupled neural network is synchronized with mixed time-delay. The considered impulsive effects can be synchronized at partly unknown transition probabilities. Besides, a multiple integral approach is also proposed to strengthen the Markovian jumping randomly coupled neural networks with partly unknown transition probabilities. By making use of Kronecker product and some useful integral inequalities, a novel Lyapunov-Krasovskii functional was designed for handling the coupled neural network with mixed delay and then impulsive synchronization criteria are solvable in a set of linear matrix inequalities. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Understanding large multiprotein complexes: applying a multiple allosteric networks model to explain the function of the Mediator transcription complex.

    Science.gov (United States)

    Lewis, Brian A

    2010-01-15

    The regulation of transcription and of many other cellular processes involves large multi-subunit protein complexes. In the context of transcription, it is known that these complexes serve as regulatory platforms that connect activator DNA-binding proteins to a target promoter. However, there is still a lack of understanding regarding the function of these complexes. Why do multi-subunit complexes exist? What is the molecular basis of the function of their constituent subunits, and how are these subunits organized within a complex? What is the reason for physical connections between certain subunits and not others? In this article, I address these issues through a model of network allostery and its application to the eukaryotic RNA polymerase II Mediator transcription complex. The multiple allosteric networks model (MANM) suggests that protein complexes such as Mediator exist not only as physical but also as functional networks of interconnected proteins through which information is transferred from subunit to subunit by the propagation of an allosteric state known as conformational spread. Additionally, there are multiple distinct sub-networks within the Mediator complex that can be defined by their connections to different subunits; these sub-networks have discrete functions that are activated when specific subunits interact with other activator proteins.

  1. Autonomous management of a recursive area hierarchy for large scale wireless sensor networks using multiple parents

    Energy Technology Data Exchange (ETDEWEB)

    Cree, Johnathan Vee [Washington State Univ., Pullman, WA (United States); Delgado-Frias, Jose [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2016-03-01

    Large scale wireless sensor networks have been proposed for applications ranging from anomaly detection in an environment to vehicle tracking. Many of these applications require the networks to be distributed across a large geographic area while supporting three to five year network lifetimes. In order to support these requirements large scale wireless sensor networks of duty-cycled devices need a method of efficient and effective autonomous configuration/maintenance. This method should gracefully handle the synchronization tasks duty-cycled networks. Further, an effective configuration solution needs to recognize that in-network data aggregation and analysis presents significant benefits to wireless sensor network and should configure the network in a way such that said higher level functions benefit from the logically imposed structure. NOA, the proposed configuration and maintenance protocol, provides a multi-parent hierarchical logical structure for the network that reduces the synchronization workload. It also provides higher level functions with significant inherent benefits such as but not limited to: removing network divisions that are created by single-parent hierarchies, guarantees for when data will be compared in the hierarchy, and redundancies for communication as well as in-network data aggregation/analysis/storage.

  2. Multiple simultaneous fault diagnosis via hierarchical and single artificial neural networks

    International Nuclear Information System (INIS)

    Eslamloueyan, R.; Shahrokhi, M.; Bozorgmehri, R.

    2003-01-01

    Process fault diagnosis involves interpreting the current status of the plant given sensor reading and process knowledge. There has been considerable work done in this area with a variety of approaches being proposed for process fault diagnosis. Neural networks have been used to solve process fault diagnosis problems in chemical process, as they are well suited for recognizing multi-dimensional nonlinear patterns. In this work, the use of Hierarchical Artificial Neural Networks in diagnosing the multi-faults of a chemical process are discussed and compared with that of Single Artificial Neural Networks. The lower efficiency of Hierarchical Artificial Neural Networks , in comparison to Single Artificial Neural Networks, in process fault diagnosis is elaborated and analyzed. Also, the concept of a multi-level selection switch is presented and developed to improve the performance of hierarchical artificial neural networks. Simulation results indicate that application of multi-level selection switch increase the performance of the hierarchical artificial neural networks considerably

  3. Universal principles governing multiple random searchers on complex networks: The logarithmic growth pattern and the harmonic law

    Science.gov (United States)

    Weng, Tongfeng; Zhang, Jie; Small, Michael; Harandizadeh, Bahareh; Hui, Pan

    2018-03-01

    We propose a unified framework to evaluate and quantify the search time of multiple random searchers traversing independently and concurrently on complex networks. We find that the intriguing behaviors of multiple random searchers are governed by two basic principles—the logarithmic growth pattern and the harmonic law. Specifically, the logarithmic growth pattern characterizes how the search time increases with the number of targets, while the harmonic law explores how the search time of multiple random searchers varies relative to that needed by individual searchers. Numerical and theoretical results demonstrate these two universal principles established across a broad range of random search processes, including generic random walks, maximal entropy random walks, intermittent strategies, and persistent random walks. Our results reveal two fundamental principles governing the search time of multiple random searchers, which are expected to facilitate investigation of diverse dynamical processes like synchronization and spreading.

  4. Multiple ECG Fiducial Points-Based Random Binary Sequence Generation for Securing Wireless Body Area Networks.

    Science.gov (United States)

    Zheng, Guanglou; Fang, Gengfa; Shankaran, Rajan; Orgun, Mehmet A; Zhou, Jie; Qiao, Li; Saleem, Kashif

    2017-05-01

    Generating random binary sequences (BSes) is a fundamental requirement in cryptography. A BS is a sequence of N bits, and each bit has a value of 0 or 1. For securing sensors within wireless body area networks (WBANs), electrocardiogram (ECG)-based BS generation methods have been widely investigated in which interpulse intervals (IPIs) from each heartbeat cycle are processed to produce BSes. Using these IPI-based methods to generate a 128-bit BS in real time normally takes around half a minute. In order to improve the time efficiency of such methods, this paper presents an ECG multiple fiducial-points based binary sequence generation (MFBSG) algorithm. The technique of discrete wavelet transforms is employed to detect arrival time of these fiducial points, such as P, Q, R, S, and T peaks. Time intervals between them, including RR, RQ, RS, RP, and RT intervals, are then calculated based on this arrival time, and are used as ECG features to generate random BSes with low latency. According to our analysis on real ECG data, these ECG feature values exhibit the property of randomness and, thus, can be utilized to generate random BSes. Compared with the schemes that solely rely on IPIs to generate BSes, this MFBSG algorithm uses five feature values from one heart beat cycle, and can be up to five times faster than the solely IPI-based methods. So, it achieves a design goal of low latency. According to our analysis, the complexity of the algorithm is comparable to that of fast Fourier transforms. These randomly generated ECG BSes can be used as security keys for encryption or authentication in a WBAN system.

  5. Multiple Linear Regression and Artificial Neural Network to Predict Blood Glucose in Overweight Patients.

    Science.gov (United States)

    Wang, J; Wang, F; Liu, Y; Xu, J; Lin, H; Jia, B; Zuo, W; Jiang, Y; Hu, L; Lin, F

    2016-01-01

    Overweight individuals are at higher risk for developing type II diabetes than the general population. We conducted this study to analyze the correlation between blood glucose and biochemical parameters, and developed a blood glucose prediction model tailored to overweight patients. A total of 346 overweight Chinese people patients ages 18-81 years were involved in this study. Their levels of fasting glucose (fs-GLU), blood lipids, and hepatic and renal functions were measured and analyzed by multiple linear regression (MLR). Based the MLR results, we developed a back propagation artificial neural network (BP-ANN) model by selecting tansig as the transfer function of the hidden layers nodes, and purelin for the output layer nodes, with training goal of 0.5×10(-5). There was significant correlation between fs-GLU with age, BMI, and blood biochemical indexes (P<0.05). The results of MLR analysis indicated that age, fasting alanine transaminase (fs-ALT), blood urea nitrogen (fs-BUN), total protein (fs-TP), uric acid (fs-BUN), and BMI are 6 independent variables related to fs-GLU. Based on these parameters, the BP-ANN model was performed well and reached high prediction accuracy when training 1 000 epoch (R=0.9987). The level of fs-GLU was predictable using the proposed BP-ANN model based on 6 related parameters (age, fs-ALT, fs-BUN, fs-TP, fs-UA and BMI) in overweight patients. © Georg Thieme Verlag KG Stuttgart · New York.

  6. Performance of Non-Orthogonal Multiple Access (NOMA) in mmWave wireless communications for 5G networks

    DEFF Research Database (Denmark)

    Marcano, Andrea; Christiansen, Henrik Lehrmann

    2017-01-01

    Among the key technologies that have been identified as capacity boosters for fifth generation - 5G - mobile networks, are millimeter wave (mmWave) transmissions and non-orthogonal multiple access (NOMA). The large amount of spectrum available at mmWave frequencies combined with a more effective...... use of available resources, helps improving the overall capacity. NOMA, unlike orthogonal multiple access (OMA) methods, allows sharing the same frequency resources at the same time, by implementing adaptive power allocation. In this paper we present a performance analysis of NOMA in mmWave cells...

  7. A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

    Directory of Open Access Journals (Sweden)

    Ji She

    2016-12-01

    Full Text Available Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance.

  8. Study and development of the data transfer for the NA50 experiment: transputer network of the multiplicity detector

    International Nuclear Information System (INIS)

    Capony, V.

    1996-01-01

    This thesis presents the works performed for the experiment NA50 at CERN, in he framework of the development of its multiplicity detector. The two first chapters describe the physical aims of the experiment and the apparatus used. The remaining part of this document shows the data readout device, developed for the multiplicity detector. Built on a T8 transputer network, this system is able to treat 8 Mbytes of data at each SPS accelerator cycle. It integrates an on-line event-builder. A filtering algorithm estimates the validity of the information and allows the flagging of all the data. The last function of this transputers network is to transfer data from the detector to the data acquisition system. Our system is able to control a data rate transfer of 35 Gbytes per day. (author)

  9. A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural Networks

    Directory of Open Access Journals (Sweden)

    Hamidreza Mousavi

    2017-01-01

    Full Text Available Recently different approaches have been developed in the field of sensor fault diagnostics based on Auto-Associative Neural Network (AANN. In this paper we present a novel algorithm called Self reconstructing Auto-Associative Neural Network (S-AANN which is able to detect and isolate single faulty sensor via reconstruction. We have also extended the algorithm to be applicable in multiple fault conditions. The algorithm uses a calibration model based on AANN. AANN can reconstruct the faulty sensor using non-faulty sensors due to correlation between the process variables, and mean of the difference between reconstructed and original data determines which sensors are faulty. The algorithms are tested on a Dimerization process. The simulation results show that the S-AANN can isolate multiple faulty sensors with low computational time that make the algorithm appropriate candidate for online applications.

  10. Electro-optical time gating based on Mach-Zehnder modulator for multiple access interference elimination in optical code-division multiple access networks

    Science.gov (United States)

    Chen, Yinfang; Wang, Rong; Fang, Tao; Pu, Tao; Xiang, Peng; Zheng, Jilin; Zhu, Huatao

    2014-05-01

    An electro-optical time gating technique, which is based on an electrical return-to-zero (RZ) pulse driven Mach-Zehnder modulator (MZM) for eliminating multiple access interference (MAI) in optical code-division multiple access (OCDMA) networks is proposed. This technique is successfully simulated in an eight-user two-dimensional wavelength-hopping time-spreading system, as well as in a three-user temporal phase encoding system. Results show that in both systems the MAI noise is efficiently removed and the average received power penalty improved. Both achieve error-free transmissions at a bit rate of 2.5 Gb/s. In addition, we also individually discuss effects of parameters in two systems, such as the extinction ratio of the MZM, the duty cycle of the driven RZ pulse, and the time misalignment between the driven pulse and the decoded autocorrelation peak, on the output bit error rate performance. Our work shows that employing a common MZM as a thresholder provides another probability and an interesting cost-effective choice for a smart size, low energy, and less complex thresholding technique for integrated detection in OCDMA networks.

  11. From struggles to resource gains in interprofessional service networks: Key findings from a multiple case study.

    Science.gov (United States)

    Toiviainen, Hanna; Kira, Mari

    2017-07-01

    In interprofessional service networks, employees cross professional boundaries to collaborate with colleagues and clients with expertise and values different from their own. It can be a struggle to adopt shared work practices and deal with "multivoicedness." At the same time, networks allow members to engage in meaningful service provision, gain a broader understanding of the service provided, and obtain social support. Intertwined network struggles and resource gains have received limited attention in the interprofessional care literature to date. The aim of the study was to investigate the learning potential of the co-existing struggles and resource gains. This article reports findings from two interprofessional networks. Interviews were conducted with 19 employees and thematically analysed. Three types of struggles and six types of resource gains of networking were identified. The struggles relate, first, to the assumptions of networking following similar practices to those in a home organisation; second, to the challenges of dealing with the multivoicedness of networking; and, third, to the experienced gap between the networking ideals and the reality of cooperation. At the same time, the network members experience gains in emotional resources (e.g., stronger sense of meaningfulness at work), cognitive resources (e.g., understanding the customer needs from alternative perspectives), and social resources (e.g., being able to rely on other professionals' competence). Learning potential emerged from the dynamics between coexisting struggles and resource gains.

  12. Perspective: Markov models for long-timescale biomolecular dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Schwantes, C. R.; McGibbon, R. T. [Department of Chemistry, Stanford University, Stanford, California 94305 (United States); Pande, V. S., E-mail: pande@stanford.edu [Department of Chemistry, Stanford University, Stanford, California 94305 (United States); Department of Computer Science, Stanford University, Stanford, California 94305 (United States); Department of Structural Biology, Stanford University, Stanford, California 94305 (United States); Biophysics Program, Stanford University, Stanford, California 94305 (United States)

    2014-09-07

    Molecular dynamics simulations have the potential to provide atomic-level detail and insight to important questions in chemical physics that cannot be observed in typical experiments. However, simply generating a long trajectory is insufficient, as researchers must be able to transform the data in a simulation trajectory into specific scientific insights. Although this analysis step has often been taken for granted, it deserves further attention as large-scale simulations become increasingly routine. In this perspective, we discuss the application of Markov models to the analysis of large-scale biomolecular simulations. We draw attention to recent improvements in the construction of these models as well as several important open issues. In addition, we highlight recent theoretical advances that pave the way for a new generation of models of molecular kinetics.

  13. ANCA: Anharmonic Conformational Analysis of Biomolecular Simulations.

    Science.gov (United States)

    Parvatikar, Akash; Vacaliuc, Gabriel S; Ramanathan, Arvind; Chennubhotla, S Chakra

    2018-05-08

    Anharmonicity in time-dependent conformational fluctuations is noted to be a key feature of functional dynamics of biomolecules. Although anharmonic events are rare, long-timescale (μs-ms and beyond) simulations facilitate probing of such events. We have previously developed quasi-anharmonic analysis to resolve higher-order spatial correlations and characterize anharmonicity in biomolecular simulations. In this article, we have extended this toolbox to resolve higher-order temporal correlations and built a scalable Python package called anharmonic conformational analysis (ANCA). ANCA has modules to: 1) measure anharmonicity in the form of higher-order statistics and its variation as a function of time, 2) output a storyboard representation of the simulations to identify key anharmonic conformational events, and 3) identify putative anharmonic conformational substates and visualization of transitions between these substates. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  14. Orientation of biomolecular assemblies in a microfluidic jet

    International Nuclear Information System (INIS)

    Priebe, M; Kalbfleisch, S; Tolkiehn, M; Salditt, T; Koester, S; Abel, B; Davies, R J

    2010-01-01

    We have investigated multilamellar lipid assemblies in a microfluidic jet, operating at high shear rates of the order of 10 7 s -1 . Compared to classical Couette cells or rheometers, the shear rate was increased by at least 2-3 orders of magnitude, and the sample volume was scaled down correspondingly. At the same time, the jet is characterized by high extensional stress due to elongational flow. A focused synchrotron x-ray beam was used to measure the structure and orientation of the lipid assemblies in the jet. The diffraction patterns indicate conventional multilamellar phases, aligned with the membrane normals oriented along the velocity gradient of the jet. The results indicate that the setup may be well suited for coherent diffractive imaging of oriented biomolecular assemblies and macromolecules at the future x-ray free electron laser (XFEL) sources.

  15. DNA-assisted swarm control in a biomolecular motor system.

    Science.gov (United States)

    Keya, Jakia Jannat; Suzuki, Ryuhei; Kabir, Arif Md Rashedul; Inoue, Daisuke; Asanuma, Hiroyuki; Sada, Kazuki; Hess, Henry; Kuzuya, Akinori; Kakugo, Akira

    2018-01-31

    In nature, swarming behavior has evolved repeatedly among motile organisms because it confers a variety of beneficial emergent properties. These include improved information gathering, protection from predators, and resource utilization. Some organisms, e.g., locusts, switch between solitary and swarm behavior in response to external stimuli. Aspects of swarming behavior have been demonstrated for motile supramolecular systems composed of biomolecular motors and cytoskeletal filaments, where cross-linkers induce large scale organization. The capabilities of such supramolecular systems may be further extended if the swarming behavior can be programmed and controlled. Here, we demonstrate that the swarming of DNA-functionalized microtubules (MTs) propelled by surface-adhered kinesin motors can be programmed and reversibly regulated by DNA signals. Emergent swarm behavior, such as translational and circular motion, can be selected by tuning the MT stiffness. Photoresponsive DNA containing azobenzene groups enables switching between solitary and swarm behavior in response to stimulation with visible or ultraviolet light.

  16. Review of MEMS differential scanning calorimetry for biomolecular study

    Science.gov (United States)

    Yu, Shifeng; Wang, Shuyu; Lu, Ming; Zuo, Lei

    2017-12-01

    Differential scanning calorimetry (DSC) is one of the few techniques that allow direct determination of enthalpy values for binding reactions and conformational transitions in biomolecules. It provides the thermodynamics information of the biomolecules which consists of Gibbs free energy, enthalpy and entropy in a straightforward manner that enables deep understanding of the structure function relationship in biomolecules such as the folding/unfolding of protein and DNA, and ligand bindings. This review provides an up to date overview of the applications of DSC in biomolecular study such as the bovine serum albumin denaturation study, the relationship between the melting point of lysozyme and the scanning rate. We also introduce the recent advances of the development of micro-electro-mechanic-system (MEMS) based DSCs.

  17. Techniques of biomolecular quantification through AMS detection of radiocarbon

    International Nuclear Information System (INIS)

    Vogel, S.J.; Turteltaub, K.W.; Frantz, C.; Felton, J.S.; Gledhill, B.L.

    1992-01-01

    Accelerator mass spectrometry offers a large gain over scintillation counting in sensitivity for detecting radiocarbon in biomolecular tracing. Application of this sensitivity requires new considerations of procedures to extract or isolate the carbon fraction to be quantified, to inventory all carbon in the sample, to prepare graphite from the sample for use in the spectrometer, and to derive a meaningful quantification from the measured isotope ratio. These procedures need to be accomplished without contaminating the sample with radiocarbon, which may be ubiquitous in laboratories and on equipment previously used for higher dose, scintillation experiments. Disposable equipment, materials and surfaces are used to control these contaminations. Quantification of attomole amounts of labeled substances are possible through these techniques

  18. Perspective: Markov models for long-timescale biomolecular dynamics

    International Nuclear Information System (INIS)

    Schwantes, C. R.; McGibbon, R. T.; Pande, V. S.

    2014-01-01

    Molecular dynamics simulations have the potential to provide atomic-level detail and insight to important questions in chemical physics that cannot be observed in typical experiments. However, simply generating a long trajectory is insufficient, as researchers must be able to transform the data in a simulation trajectory into specific scientific insights. Although this analysis step has often been taken for granted, it deserves further attention as large-scale simulations become increasingly routine. In this perspective, we discuss the application of Markov models to the analysis of large-scale biomolecular simulations. We draw attention to recent improvements in the construction of these models as well as several important open issues. In addition, we highlight recent theoretical advances that pave the way for a new generation of models of molecular kinetics

  19. Hybrid organic semiconductor lasers for bio-molecular sensing.

    Science.gov (United States)

    Haughey, Anne-Marie; Foucher, Caroline; Guilhabert, Benoit; Kanibolotsky, Alexander L; Skabara, Peter J; Burley, Glenn; Dawson, Martin D; Laurand, Nicolas

    2014-01-01

    Bio-functionalised luminescent organic semiconductors are attractive for biophotonics because they can act as efficient laser materials while simultaneously interacting with molecules. In this paper, we present and discuss a laser biosensor platform that utilises a gain layer made of such an organic semiconductor material. The simple structure of the sensor and its operation principle are described. Nanolayer detection is shown experimentally and analysed theoretically in order to assess the potential and the limits of the biosensor. The advantage conferred by the organic semiconductor is explained, and comparisons to laser sensors using alternative dye-doped materials are made. Specific biomolecular sensing is demonstrated, and routes to functionalisation with nucleic acid probes, and future developments opened up by this achievement, are highlighted. Finally, attractive formats for sensing applications are mentioned, as well as colloidal quantum dots, which in the future could be used in conjunction with organic semiconductors.

  20. THz time domain spectroscopy of biomolecular conformational modes

    International Nuclear Information System (INIS)

    Markelz, Andrea; Whitmire, Scott; Hillebrecht, Jay; Birge, Robert

    2002-01-01

    We discuss the use of terahertz time domain spectroscopy for studies of conformational flexibility and conformational change in biomolecules. Protein structural dynamics are vital to biological function with protein flexibility affecting enzymatic reaction rates and sensory transduction cycling times. Conformational mode dynamics occur on the picosecond timescale and with the collective vibrational modes associated with these large scale structural motions in the 1-100 cm -1 range. We have performed THz time domain spectroscopy (TTDS) of several biomolecular systems to explore the sensitivity of TTDS to distinguish different molecular species, different mutations within a single species and different conformations of a given biomolecule. We compare the measured absorbances to normal mode calculations and find that the TTDS absorbance reflects the density of normal modes determined by molecular mechanics calculations, and is sensitive to both conformation and mutation. These early studies demonstrate some of the advantages and limitations of using TTDS for the study of biomolecules

  1. Design rules for biomolecular adhesion: lessons from force measurements.

    Science.gov (United States)

    Leckband, Deborah

    2010-01-01

    Cell adhesion to matrix, other cells, or pathogens plays a pivotal role in many processes in biomolecular engineering. Early macroscopic methods of quantifying adhesion led to the development of quantitative models of cell adhesion and migration. The more recent use of sensitive probes to quantify the forces that alter or manipulate adhesion proteins has revealed much greater functional diversity than was apparent from population average measurements of cell adhesion. This review highlights theoretical and experimental methods that identified force-dependent molecular properties that are central to the biological activity of adhesion proteins. Experimental and theoretical methods emphasized in this review include the surface force apparatus, atomic force microscopy, and vesicle-based probes. Specific examples given illustrate how these tools have revealed unique properties of adhesion proteins and their structural origins.

  2. High-speed AFM for Studying Dynamic Biomolecular Processes

    Science.gov (United States)

    Ando, Toshio

    2008-03-01

    Biological molecules show their vital activities only in aqueous solutions. It had been one of dreams in biological sciences to directly observe biological macromolecules (protein, DNA) at work under a physiological condition because such observation is straightforward to understanding their dynamic behaviors and functional mechanisms. Optical microscopy has no sufficient spatial resolution and electron microscopy is not applicable to in-liquid samples. Atomic force microscopy (AFM) can visualize molecules in liquids at high resolution but its imaging rate was too low to capture dynamic biological processes. This slow imaging rate is because AFM employs mechanical probes (cantilevers) and mechanical scanners to detect the sample height at each pixel. It is quite difficult to quickly move a mechanical device of macroscopic size with sub-nanometer accuracy without producing unwanted vibrations. It is also difficult to maintain the delicate contact between a probe tip and fragile samples. Two key techniques are required to realize high-speed AFM for biological research; fast feedback control to maintain a weak tip-sample interaction force and a technique to suppress mechanical vibrations of the scanner. Various efforts have been carried out in the past decade to materialize high-speed AFM. The current high-speed AFM can capture images on video at 30-60 frames/s for a scan range of 250nm and 100 scan lines, without significantly disturbing week biomolecular interaction. Our recent studies demonstrated that this new microscope can reveal biomolecular processes such as myosin V walking along actin tracks and association/dissociation dynamics of chaperonin GroEL-GroES that occurs in a negatively cooperative manner. The capacity of nanometer-scale visualization of dynamic processes in liquids will innovate on biological research. In addition, it will open a new way to study dynamic chemical/physical processes of various phenomena that occur at the liquid-solid interfaces.

  3. Integration of biomolecular logic gates with field-effect transducers

    Energy Technology Data Exchange (ETDEWEB)

    Poghossian, A., E-mail: a.poghossian@fz-juelich.de [Institute of Nano- and Biotechnologies, Aachen University of Applied Sciences, Campus Juelich, Heinrich-Mussmann-Str. 1, D-52428 Juelich (Germany); Institute of Bio- and Nanosystems, Research Centre Juelich GmbH, D-52425 Juelich (Germany); Malzahn, K. [Institute of Nano- and Biotechnologies, Aachen University of Applied Sciences, Campus Juelich, Heinrich-Mussmann-Str. 1, D-52428 Juelich (Germany); Abouzar, M.H. [Institute of Nano- and Biotechnologies, Aachen University of Applied Sciences, Campus Juelich, Heinrich-Mussmann-Str. 1, D-52428 Juelich (Germany); Institute of Bio- and Nanosystems, Research Centre Juelich GmbH, D-52425 Juelich (Germany); Mehndiratta, P. [Institute of Nano- and Biotechnologies, Aachen University of Applied Sciences, Campus Juelich, Heinrich-Mussmann-Str. 1, D-52428 Juelich (Germany); Katz, E. [Department of Chemistry and Biomolecular Science, NanoBio Laboratory (NABLAB), Clarkson University, Potsdam, NY 13699-5810 (United States); Schoening, M.J. [Institute of Nano- and Biotechnologies, Aachen University of Applied Sciences, Campus Juelich, Heinrich-Mussmann-Str. 1, D-52428 Juelich (Germany); Institute of Bio- and Nanosystems, Research Centre Juelich GmbH, D-52425 Juelich (Germany)

    2011-11-01

    Highlights: > Enzyme-based AND/OR logic gates are integrated with a capacitive field-effect sensor. > The AND/OR logic gates compose of multi-enzyme system immobilised on sensor surface. > Logic gates were activated by different combinations of chemical inputs (analytes). > The logic output (pH change) produced by the enzymes was read out by the sensor. - Abstract: The integration of biomolecular logic gates with field-effect devices - the basic element of conventional electronic logic gates and computing - is one of the most attractive and promising approaches for the transformation of biomolecular logic principles into macroscopically useable electrical output signals. In this work, capacitive field-effect EIS (electrolyte-insulator-semiconductor) sensors based on a p-Si-SiO{sub 2}-Ta{sub 2}O{sub 5} structure modified with a multi-enzyme membrane have been used for electronic transduction of biochemical signals processed by enzyme-based OR and AND logic gates. The realised OR logic gate composes of two enzymes (glucose oxidase and esterase) and was activated by ethyl butyrate or/and glucose. The AND logic gate composes of three enzymes (invertase, mutarotase and glucose oxidase) and was activated by two chemical input signals: sucrose and dissolved oxygen. The developed integrated enzyme logic gates produce local pH changes at the EIS sensor surface as a result of biochemical reactions activated by different combinations of chemical input signals, while the pH value of the bulk solution remains unchanged. The pH-induced charge changes at the gate-insulator (Ta{sub 2}O{sub 5}) surface of the EIS transducer result in an electronic signal corresponding to the logic output produced by the immobilised enzymes. The logic output signals have been read out by means of a constant-capacitance method.

  4. Integration of biomolecular logic gates with field-effect transducers

    International Nuclear Information System (INIS)

    Poghossian, A.; Malzahn, K.; Abouzar, M.H.; Mehndiratta, P.; Katz, E.; Schoening, M.J.

    2011-01-01

    Highlights: → Enzyme-based AND/OR logic gates are integrated with a capacitive field-effect sensor. → The AND/OR logic gates compose of multi-enzyme system immobilised on sensor surface. → Logic gates were activated by different combinations of chemical inputs (analytes). → The logic output (pH change) produced by the enzymes was read out by the sensor. - Abstract: The integration of biomolecular logic gates with field-effect devices - the basic element of conventional electronic logic gates and computing - is one of the most attractive and promising approaches for the transformation of biomolecular logic principles into macroscopically useable electrical output signals. In this work, capacitive field-effect EIS (electrolyte-insulator-semiconductor) sensors based on a p-Si-SiO 2 -Ta 2 O 5 structure modified with a multi-enzyme membrane have been used for electronic transduction of biochemical signals processed by enzyme-based OR and AND logic gates. The realised OR logic gate composes of two enzymes (glucose oxidase and esterase) and was activated by ethyl butyrate or/and glucose. The AND logic gate composes of three enzymes (invertase, mutarotase and glucose oxidase) and was activated by two chemical input signals: sucrose and dissolved oxygen. The developed integrated enzyme logic gates produce local pH changes at the EIS sensor surface as a result of biochemical reactions activated by different combinations of chemical input signals, while the pH value of the bulk solution remains unchanged. The pH-induced charge changes at the gate-insulator (Ta 2 O 5 ) surface of the EIS transducer result in an electronic signal corresponding to the logic output produced by the immobilised enzymes. The logic output signals have been read out by means of a constant-capacitance method.

  5. Distributed Containment Control for Multiple Unknown Second-Order Nonlinear Systems With Application to Networked Lagrangian Systems.

    Science.gov (United States)

    Mei, Jie; Ren, Wei; Li, Bing; Ma, Guangfu

    2015-09-01

    In this paper, we consider the distributed containment control problem for multiagent systems with unknown nonlinear dynamics. More specifically, we focus on multiple second-order nonlinear systems and networked Lagrangian systems. We first study the distributed containment control problem for multiple second-order nonlinear systems with multiple dynamic leaders in the presence of unknown nonlinearities and external disturbances under a general directed graph that characterizes the interaction among the leaders and the followers. A distributed adaptive control algorithm with an adaptive gain design based on the approximation capability of neural networks is proposed. We present a necessary and sufficient condition on the directed graph such that the containment error can be reduced as small as desired. As a byproduct, the leaderless consensus problem is solved with asymptotical convergence. Because relative velocity measurements between neighbors are generally more difficult to obtain than relative position measurements, we then propose a distributed containment control algorithm without using neighbors' velocity information. A two-step Lyapunov-based method is used to study the convergence of the closed-loop system. Next, we apply the ideas to deal with the containment control problem for networked unknown Lagrangian systems under a general directed graph. All the proposed algorithms are distributed and can be implemented using only local measurements in the absence of communication. Finally, simulation examples are provided to show the effectiveness of the proposed control algorithms.

  6. A neuromorphic implementation of multiple spike-timing synaptic plasticity rules for large-scale neural networks

    Directory of Open Access Journals (Sweden)

    Runchun Mark Wang

    2015-05-01

    Full Text Available We present a neuromorphic implementation of multiple synaptic plasticity learning rules, which include both Spike Timing Dependent Plasticity (STDP and Spike Timing Dependent Delay Plasticity (STDDP. We present a fully digital implementation as well as a mixed-signal implementation, both of which use a novel dynamic-assignment time-multiplexing approach and support up to 2^26 (64M synaptic plasticity elements. Rather than implementing dedicated synapses for particular types of synaptic plasticity, we implemented a more generic synaptic plasticity adaptor array that is separate from the neurons in the neural network. Each adaptor performs synaptic plasticity according to the arrival times of the pre- and post-synaptic spikes assigned to it, and sends out a weighted and/or delayed pre-synaptic spike to the target synapse in the neural network. This strategy provides great flexibility for building complex large-scale neural networks, as a neural network can be configured for multiple synaptic plasticity rules without changing its structure. We validate the proposed neuromorphic implementations with measurement results and illustrate that the circuits are capable of performing both STDP and STDDP. We argue that it is practical to scale the work presented here up to 2^36 (64G synaptic adaptors on a current high-end FPGA platform.

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

    DEFF Research Database (Denmark)

    Tao, Haidong; Hu, Haitao; Wang, Xiongfei

    2018-01-01

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

  8. Improved Iterative Decoding of Network-Channel Codes for Multiple-Access Relay Channel.

    Science.gov (United States)

    Majumder, Saikat; Verma, Shrish

    2015-01-01

    Cooperative communication using relay nodes is one of the most effective means of exploiting space diversity for low cost nodes in wireless network. In cooperative communication, users, besides communicating their own information, also relay the information of other users. In this paper we investigate a scheme where cooperation is achieved using a common relay node which performs network coding to provide space diversity for two information nodes transmitting to a base station. We propose a scheme which uses Reed-Solomon error correcting code for encoding the information bit at the user nodes and convolutional code as network code, instead of XOR based network coding. Based on this encoder, we propose iterative soft decoding of joint network-channel code by treating it as a concatenated Reed-Solomon convolutional code. Simulation results show significant improvement in performance compared to existing scheme based on compound codes.

  9. A Study on Integrated Control Network for Multiple Automation Services-1st year report

    Energy Technology Data Exchange (ETDEWEB)

    Hyun, D.H.; Park, B.S.; Kim, M.S.; Lim, Y.H.; Ahn, S.K. [Korea Electric Power Research Institute, Taejon (Korea)

    2002-07-01

    This report describes the development of Integrated and Intelligent Gateway which is under developed. The network operating technique in this report can identifies the causes of the communication faults and can avoid communication network faults in advance. Utility companies spend large financial investment and time for supplying the stabilized power. Since this is deeply related to the reliability of Automation Systems, it is natural to employ Fault-Tolerant communication network for Automation Systems. Use of the network system developed in this report is not limited in DAS. It can be expandable to the many kinds of data services for customer. Thus this report suggests the direction of the communication network development. This 1st year report is composed of following contents, 1) The introduction and problems of DAS. 2) The configuration and functions of IIG. 3) The protocols. (author). 27 refs., 73 figs., 6 tabs.

  10. Improving the Reliability of Optimised Link State Routing in a Smart Grid Neighbour Area Network based Wireless Mesh Network Using Multiple Metrics

    Directory of Open Access Journals (Sweden)

    Yakubu Tsado

    2017-02-01

    Full Text Available Reliable communication is the backbone of advanced metering infrastructure (AMI. Within the AMI, the neighbourhood area network (NAN transports a multitude of traffic, each with unique requirements. In order to deliver an acceptable level of reliability and latency, the underlying network, such as the wireless mesh network(WMN, must provide or guarantee the quality-of-service (QoS level required by the respective application traffic. Existing WMN routing protocols, such as optimised link state routing (OLSR, typically utilise a single metric and do not consider the requirements of individual traffic; hence, packets are delivered on a best-effort basis. This paper presents a QoS-aware WMN routing technique that employs multiple metrics in OLSR optimal path selection for AMI applications. The problems arising from this approach are non deterministic polynomial time (NP-complete in nature, which were solved through the combined use of the analytical hierarchy process (AHP algorithm and pruning techniques. For smart meters transmitting Internet Protocol (IP packets of varying sizes at different intervals, the proposed technique considers the constraints of NAN and the applications’ traffic characteristics. The technique was developed by combining multiple OLSR path selection metrics with the AHP algorithminns-2. Compared with the conventional link metric in OLSR, the results show improvements of about 23% and 45% in latency and Packet Delivery Ratio (PDR, respectively, in a 25-node grid NAN.

  11. Proceedings of the international advisory committee on 'biomolecular dynamics instrument DNA' and the workshop on 'biomolecular dynamics backscattering spectrometers'

    International Nuclear Information System (INIS)

    Arai, Masatoshi; Aizawa, Kazuya; Nakajima, Kenji; Shibata, Kaoru; Takahashi, Nobuaki

    2008-08-01

    A workshop entitled 'Biomolecular Dynamics Backscattering Spectrometers' was held on February 27th - 29th, 2008 at J-PARC Center, Japan Atomic Energy Agency. This workshop was planned to be held for aiming to realize an innovative neutron backscattering instrument, namely DNA, in the MLF and thus four leading scientists in the field of neutron backscattering instruments were invited as the International Advisory Committee (IAC member: Dr. Dan Neumann (Chair); Prof. Ferenc Mezei; Dr. Hannu Mutka; Dr. Philip Tregenna-Piggott) for DNA from institutes in the United States, France and Switzerland, where backscattering instruments are in-service. It was therefore held in the form of lecture anterior and then in the form of the committee posterior. This report includes the executive summary of the IAC and materials of the presentations in the IAC and the workshop. (author)

  12. Oscillation-Driven Spike-Timing Dependent Plasticity Allows Multiple Overlapping Pattern Recognition in Inhibitory Interneuron Networks

    DEFF Research Database (Denmark)

    Garrido, Jesús A.; Luque, Niceto R.; Tolu, Silvia

    2016-01-01

    The majority of operations carried out by the brain require learning complex signal patterns for future recognition, retrieval and reuse. Although learning is thought to depend on multiple forms of long-term synaptic plasticity, the way this latter contributes to pattern recognition is still poorly...... and at the inhibitory interneuron-interneuron synapses, the interneurons rapidly learned complex input patterns. Interestingly, induction of plasticity required that the network be entrained into theta-frequency band oscillations, setting the internal phase-reference required to drive STDP. Inhibitory plasticity...... effectively distributed multiple patterns among available interneurons, thus allowing the simultaneous detection of multiple overlapping patterns. The addition of plasticity in intrinsic excitability made the system more robust allowing self-adjustment and rescaling in response to a broad range of input...

  13. A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design.

    Science.gov (United States)

    Alford, Rebecca F; Leaver-Fay, Andrew; Gonzales, Lynda; Dolan, Erin L; Gray, Jeffrey J

    2017-12-01

    Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology.

  14. A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design.

    Directory of Open Access Journals (Sweden)

    Rebecca F Alford

    2017-12-01

    Full Text Available Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology.

  15. Versatile single-molecule multi-color excitation and detection fluorescence setup for studying biomolecular dynamics

    KAUST Repository

    Sobhy, M. A.; Elshenawy, M. M.; Takahashi, Masateru; Whitman, B. H.; Walter, N. G.; Hamdan, S. M.

    2011-01-01

    Single-molecule fluorescence imaging is at the forefront of tools applied to study biomolecular dynamics both in vitro and in vivo. The ability of the single-molecule fluorescence microscope to conduct simultaneous multi-color excitation

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

    International Nuclear Information System (INIS)

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

    2006-01-01

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

  17. Performance analysis of an opportunistic multi-user cognitive network with multiple primary users

    KAUST Repository

    Khan, Fahd Ahmed; Tourki, Kamel; Alouini, Mohamed-Slim; Qaraqe, Khalid A.

    2014-01-01

    constraint is imposed on the secondary network in addition to the limited peak transmit power of each SU. The uplink scenario is considered where a single SU is selected for transmission. This opportunistic selection depends on the transmission channel power

  18. Report of the European Myeloma Network on multiparametric flow cytometry in multiple myeloma and related disorders

    DEFF Research Database (Denmark)

    Rawstron, Andy C; Orfao, Alberto; Beksac, Meral

    2008-01-01

    The European Myeloma Network (EMN) organized two flow cytometry workshops. The first aimed to identify specific indications for flow cytometry in patients with monoclonal gammopathies, and consensus technical approaches through a questionnaire-based review of current practice in participating...

  19. Optimized green operation of LTE networks in the presence of multiple electricity providers

    KAUST Repository

    Ghazzai, Hakim

    2012-12-01

    Energy efficiency aspects in cellular networks can significantly contribute to the reduction of greenhouse gas emissions and help to save the environment. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Besides, introducing renewable energies as alternative power sources becomes a real challenge to network operators. In this paper, we propose a method that reduces the energy consumption of BSs by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from different retailers (Renewable energy and electricity retailers). We formulate an optimization problem that leads to the maximization of the profit of a Long-Term Evolution (LTE) cellular operator, and at the same time to the minimization of CO2 emissions in green wireless cellular networks without affecting the desired Quality of Service. © 2012 IEEE.

  20. Optimized green operation of LTE networks in the presence of multiple electricity providers

    KAUST Repository

    Ghazzai, Hakim; Yaacoub, Elias E.; Alouini, Mohamed-Slim; Abu-Dayya, Adnan A.

    2012-01-01

    Energy efficiency aspects in cellular networks can significantly contribute to the reduction of greenhouse gas emissions and help to save the environment. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Besides, introducing renewable energies as alternative power sources becomes a real challenge to network operators. In this paper, we propose a method that reduces the energy consumption of BSs by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from different retailers (Renewable energy and electricity retailers). We formulate an optimization problem that leads to the maximization of the profit of a Long-Term Evolution (LTE) cellular operator, and at the same time to the minimization of CO2 emissions in green wireless cellular networks without affecting the desired Quality of Service. © 2012 IEEE.

  1. Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system

    Science.gov (United States)

    Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.; Rocky, Durrans S.

    2000-01-01

    Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identification from core data are costly and different geologists may provide different interpretations. In this paper, we present a low-cost intelligent system consisting of three adaptive resonance theory neural networks and a rule-based expert system to consistently and objectively identify lithofacies from well-log data. The input data are altered into different forms representing different perspectives of observation of lithofacies. Each form of input is processed by a different adaptive resonance theory neural network. Among these three adaptive resonance theory neural networks, one neural network processes the raw continuous data, another processes categorial data, and the third processes fuzzy-set data. Outputs from these three networks are then combined by the expert system using fuzzy inference to determine to which facies the input data should be assigned. Rules are prioritized to emphasize the importance of firing order. This new approach combines the learning ability of neural networks, the adaptability of fuzzy logic, and the expertise of geologists to infer facies of the rocks. This approach is applied to the Appleton Field, an oil field located in Escambia County, Alabama. The hybrid intelligence system predicts lithofacies identity from log data with 87.6% accuracy. This prediction is more accurate than those of single adaptive resonance theory networks, 79.3%, 68.0% and 66.0%, using raw, fuzzy-set, and categorical data, respectively, and by an error-backpropagation neural network, 57.3%. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.

  2. Global robust stability of bidirectional associative memory neural networks with multiple time delays.

    Science.gov (United States)

    Senan, Sibel; Arik, Sabri

    2007-10-01

    This correspondence presents a sufficient condition for the existence, uniqueness, and global robust asymptotic stability of the equilibrium point for bidirectional associative memory neural networks with discrete time delays. The results impose constraint conditions on the network parameters of the neural system independently of the delay parameter, and they are applicable to all bounded continuous nonmonotonic neuron activation functions. Some numerical examples are given to compare our results with the previous robust stability results derived in the literature.

  3. hPDB – Haskell library for processing atomic biomolecular structures in protein data bank format

    OpenAIRE

    Gajda, Michał Jan

    2013-01-01

    Background Protein DataBank file format is used for the majority of biomolecular data available today. Haskell is a lazy functional language that enjoys a high-level class-based type system, a growing collection of useful libraries and a reputation for efficiency. Findings I present a fast library for processing biomolecular data in the Protein Data Bank format. I present benchmarks indicating that this library is faster than other frequently used Protein Data Bank parsing programs. The propo...

  4. A compact hard X-ray source for medical imaging and biomolecular studies

    International Nuclear Information System (INIS)

    Cline, D.B.; Green, M.A.; Kolonko, J.

    1995-01-01

    There are a large number of synchrotron light sources in the world. However, these sources are designed for physics, chemistry, and engineering studies. To our knowledge, none have been optimized for either medical imaging or biomolecular studies. There are special needs for these applications. We present here a preliminary design of a very compact source, small enough for a hospital or a biomolecular laboratory, that is suitable for these applications. (orig.)

  5. Computational methods to study the structure and dynamics of biomolecules and biomolecular processes from bioinformatics to molecular quantum mechanics

    CERN Document Server

    2014-01-01

    Since the second half of the 20th century machine computations have played a critical role in science and engineering. Computer-based techniques have become especially important in molecular biology, since they often represent the only viable way to gain insights into the behavior of a biological system as a whole. The complexity of biological systems, which usually needs to be analyzed on different time- and size-scales and with different levels of accuracy, requires the application of different approaches, ranging from comparative analysis of sequences and structural databases, to the analysis of networks of interdependence between cell components and processes, through coarse-grained modeling to atomically detailed simulations, and finally to molecular quantum mechanics. This book provides a comprehensive overview of modern computer-based techniques for computing the structure, properties and dynamics of biomolecules and biomolecular processes. The twenty-two chapters, written by scientists from all over t...

  6. Phase sensitive spectral domain interferometry for label free biomolecular interaction analysis and biosensing applications

    Science.gov (United States)

    Chirvi, Sajal

    -channel label-free biosensing applications is introduced. Simultaneous interrogation of multiple biosensors is achievable with a single spectral domain phase sensitive interferometer by coding the individual sensograms in coherence-multiplexed channels. Experimental results demonstrating multiplexed quantitative biomolecular interaction analysis of antibodies binding to antigen coated functionalized biosensor chip surfaces on different platforms are presented.

  7. Modeling and Simulation of a Novel Relay Node Based Secure Routing Protocol Using Multiple Mobile Sink for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Madhumathy Perumal

    2015-01-01

    Full Text Available Data gathering and optimal path selection for wireless sensor networks (WSN using existing protocols result in collision. Increase in collision further increases the possibility of packet drop. Thus there is a necessity to eliminate collision during data aggregation. Increasing the efficiency is the need of the hour with maximum security. This paper is an effort to come up with a reliable and energy efficient WSN routing and secure protocol with minimum delay. This technique is named as relay node based secure routing protocol for multiple mobile sink (RSRPMS. This protocol finds the rendezvous point for optimal transmission of data using a “splitting tree” technique in tree-shaped network topology and then to determine all the subsequent positions of a sink the “Biased Random Walk” model is used. In case of an event, the sink gathers the data from all sources, when they are in the sensing range of rendezvous point. Otherwise relay node is selected from its neighbor to transfer packets from rendezvous point to sink. A symmetric key cryptography is used for secure transmission. The proposed relay node based secure routing protocol for multiple mobile sink (RSRPMS is experimented and simulation results are compared with Intelligent Agent-Based Routing (IAR protocol to prove that there is increase in the network lifetime compared with other routing protocols.

  8. A Hybrid Fuzzy Time Series Approach Based on Fuzzy Clustering and Artificial Neural Network with Single Multiplicative Neuron Model

    Directory of Open Access Journals (Sweden)

    Ozge Cagcag Yolcu

    2013-01-01

    Full Text Available Particularly in recent years, artificial intelligence optimization techniques have been used to make fuzzy time series approaches more systematic and improve forecasting performance. Besides, some fuzzy clustering methods and artificial neural networks with different structures are used in the fuzzification of observations and determination of fuzzy relationships, respectively. In approaches considering the membership values, the membership values are determined subjectively or fuzzy outputs of the system are obtained by considering that there is a relation between membership values in identification of relation. This necessitates defuzzification step and increases the model error. In this study, membership values were obtained more systematically by using Gustafson-Kessel fuzzy clustering technique. The use of artificial neural network with single multiplicative neuron model in identification of fuzzy relation eliminated the architecture selection problem as well as the necessity for defuzzification step by constituting target values from real observations of time series. The training of artificial neural network with single multiplicative neuron model which is used for identification of fuzzy relation step is carried out with particle swarm optimization. The proposed method is implemented using various time series and the results are compared with those of previous studies to demonstrate the performance of the proposed method.

  9. Power Flow Calculation for Weakly Meshed Distribution Networks with Multiple DGs Based on Generalized Chain-table Storage Structure

    DEFF Research Database (Denmark)

    Chen, Shuheng; Hu, Weihao; Chen, Zhe

    2014-01-01

    Based on generalized chain-table storage structure (GCTSS), a novel power flow method is proposed, which can be used to solve the power flow of weakly meshed distribution networks with multiple distributed generators (DGs). GCTSS is designed based on chain-table technology and its target is to de......Based on generalized chain-table storage structure (GCTSS), a novel power flow method is proposed, which can be used to solve the power flow of weakly meshed distribution networks with multiple distributed generators (DGs). GCTSS is designed based on chain-table technology and its target...... is to describe the topology of radial distribution networks with a clear logic and a small memory size. The strategies of compensating the equivalent currents of break-point branches and the reactive power outputs of PV-type DGs are presented on the basis of superposition theorem. Their formulations...... are simplified to be the final multi-variable linear functions. Furthermore, an accelerating factor is applied to the outer-layer reactive power compensation for improving the convergence procedure. Finally, the proposed power flow method is performed in program language VC++ 6.0, and numerical tests have been...

  10. Poisson-Nernst-Planck Equations for Simulating Biomolecular Diffusion-Reaction Processes I: Finite Element Solutions.

    Science.gov (United States)

    Lu, Benzhuo; Holst, Michael J; McCammon, J Andrew; Zhou, Y C

    2010-09-20

    In this paper we developed accurate finite element methods for solving 3-D Poisson-Nernst-Planck (PNP) equations with singular permanent charges for electrodiffusion in solvated biomolecular systems. The electrostatic Poisson equation was defined in the biomolecules and in the solvent, while the Nernst-Planck equation was defined only in the solvent. We applied a stable regularization scheme to remove the singular component of the electrostatic potential induced by the permanent charges inside biomolecules, and formulated regular, well-posed PNP equations. An inexact-Newton method was used to solve the coupled nonlinear elliptic equations for the steady problems; while an Adams-Bashforth-Crank-Nicolson method was devised for time integration for the unsteady electrodiffusion. We numerically investigated the conditioning of the stiffness matrices for the finite element approximations of the two formulations of the Nernst-Planck equation, and theoretically proved that the transformed formulation is always associated with an ill-conditioned stiffness matrix. We also studied the electroneutrality of the solution and its relation with the boundary conditions on the molecular surface, and concluded that a large net charge concentration is always present near the molecular surface due to the presence of multiple species of charged particles in the solution. The numerical methods are shown to be accurate and stable by various test problems, and are applicable to real large-scale biophysical electrodiffusion problems.

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

    Directory of Open Access Journals (Sweden)

    Liu Lili

    2013-06-01

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

  12. Evaluating multiple determinants of the structure of plant-animal mutualistic networks.

    Science.gov (United States)

    Vázquez, Diego P; Chacoff, Natacha P; Cagnolo, Luciano

    2009-08-01

    The structure of mutualistic networks is likely to result from the simultaneous influence of neutrality and the constraints imposed by complementarity in species phenotypes, phenologies, spatial distributions, phylogenetic relationships, and sampling artifacts. We develop a conceptual and methodological framework to evaluate the relative contributions of these potential determinants. Applying this approach to the analysis of a plant-pollinator network, we show that information on relative abundance and phenology suffices to predict several aggregate network properties (connectance, nestedness, interaction evenness, and interaction asymmetry). However, such information falls short of predicting the detailed network structure (the frequency of pairwise interactions), leaving a large amount of variation unexplained. Taken together, our results suggest that both relative species abundance and complementarity in spatiotemporal distribution contribute substantially to generate observed network patters, but that this information is by no means sufficient to predict the occurrence and frequency of pairwise interactions. Future studies could use our methodological framework to evaluate the generality of our findings in a representative sample of study systems with contrasting ecological conditions.

  13. Trellis Tone Modulation Multiple-Access for Peer Discovery in D2D Networks

    Directory of Open Access Journals (Sweden)

    Chiwoo Lim

    2018-04-01

    Full Text Available In this paper, a new non-orthogonal multiple-access scheme, trellis tone modulation multiple-access (TTMMA, is proposed for peer discovery of distributed device-to-device (D2D communication. The range and capacity of discovery are important performance metrics in peer discovery. The proposed trellis tone modulation uses single-tone transmission and achieves a long discovery range due to its low Peak-to-Average Power Ratio (PAPR. The TTMMA also exploits non-orthogonal resource assignment to increase the discovery capacity. For the multi-user detection of superposed multiple-access signals, a message-passing algorithm with supplementary schemes are proposed. With TTMMA and its message-passing demodulation, approximately 1.5 times the number of devices are discovered compared to the conventional frequency division multiple-access (FDMA-based discovery.

  14. A 1D thermomechanical network transition constitutive model coupled with multiple structural relaxation for shape memory polymers

    Science.gov (United States)

    Zeng, Hao; Xie, Zhimin; Gu, Jianping; Sun, Huiyu

    2018-03-01

    A new thermomechanical network transition constitutive model is proposed in the study to describe the viscoelastic behavior of shape memory polymers (SMPs). Based on the microstructure of semi-crystalline SMPs, a new simplified transformation equation is proposed to describe the transform of transient networks. And the generalized fractional Maxwell model is introduced in the paper to estimate the temperature-dependent storage modulus. In addition, a neo-KAHR theory with multiple discrete relaxation processes is put forward to study the structural relaxation of the nonlinear thermal strain in cooling/heating processes. The evolution equations of the time- and temperature-dependent stress and strain response are developed. In the model, the thermodynamical and mechanical characteristics of SMPs in the typical thermomechanical cycle are described clearly and the irreversible deformation is studied in detail. Finally, the typical thermomechanical cycles are simulated using the present constitutive model, and the simulation results agree well with the experimental results.

  15. Comparison of a neural network with multiple linear regression for quantitative analysis in ICP-atomic emission spectroscopy

    International Nuclear Information System (INIS)

    Schierle, C.; Otto, M.

    1992-01-01

    A two layer perceptron with backpropagation of error is used for quantitative analysis in ICP-AES. The network was trained by emission spectra of two interfering lines of Cd and As and the concentrations of both elements were subsequently estimated from mixture spectra. The spectra of the Cd and As lines were also used to perform multiple linear regression (MLR) via the calculation of the pseudoinverse S + of the sensitivity matrix S. In the present paper it is shown that there exist close relations between the operation of the perceptron and the MLR procedure. These are most clearly apparent in the correlation between the weights of the backpropagation network and the elements of the pseudoinverse. Using MLR, the confidence intervals over the predictions are exploited to correct for the optical device of the wavelength shift. (orig.)

  16. Modelling of multiple short-length-scale stall cells in an axial compressor using evolved GMDH neural networks

    International Nuclear Information System (INIS)

    Amanifard, N.; Nariman-Zadeh, N.; Farahani, M.H.; Khalkhali, A.

    2008-01-01

    Over the past 15 years there have been several research efforts to capture the stall inception nature in axial flow compressors. However previous analytical models could not explain the formation of short-length-scale stall cells. This paper provides a new model based on evolved GMDH neural network for transient evolution of multiple short-length-scale stall cells in an axial compressor. Genetic Algorithms (GAs) are also employed for optimal design of connectivity configuration of such GMDH-type neural networks. In this way, low-pass filter (LPF) pressure trace near the rotor leading edge is modelled with respect to the variation of pressure coefficient, flow rate coefficient, and number of rotor rotations which are defined as inputs

  17. Comparison of multiple linear regression and artificial neural network in developing the objective functions of the orthopaedic screws.

    Science.gov (United States)

    Hsu, Ching-Chi; Lin, Jinn; Chao, Ching-Kong

    2011-12-01

    Optimizing the orthopaedic screws can greatly improve their biomechanical performances. However, a methodical design optimization approach requires a long time to search the best design. Thus, the surrogate objective functions of the orthopaedic screws should be accurately developed. To our knowledge, there is no study to evaluate the strengths and limitations of the surrogate methods in developing the objective functions of the orthopaedic screws. Three-dimensional finite element models for both the tibial locking screws and the spinal pedicle screws were constructed and analyzed. Then, the learning data were prepared according to the arrangement of the Taguchi orthogonal array, and the verification data were selected with use of a randomized selection. Finally, the surrogate objective functions were developed by using either the multiple linear regression or the artificial neural network. The applicability and accuracy of those surrogate methods were evaluated and discussed. The multiple linear regression method could successfully construct the objective function of the tibial locking screws, but it failed to develop the objective function of the spinal pedicle screws. The artificial neural network method showed a greater capacity of prediction in developing the objective functions for the tibial locking screws and the spinal pedicle screws than the multiple linear regression method. The artificial neural network method may be a useful option for developing the objective functions of the orthopaedic screws with a greater structural complexity. The surrogate objective functions of the orthopaedic screws could effectively decrease the time and effort required for the design optimization process. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  18. Multiple Score Comparison: a network meta-analysis approach to comparison and external validation of prognostic scores

    Directory of Open Access Journals (Sweden)

    Sarah R. Haile

    2017-12-01

    Full Text Available Abstract Background Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them. Methods Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined. Results We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small. Conclusions We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties

  19. A comparison of multiple regression and neural network techniques for mapping in situ pCO2 data

    International Nuclear Information System (INIS)

    Lefevre, Nathalie; Watson, Andrew J.; Watson, Adam R.

    2005-01-01

    Using about 138,000 measurements of surface pCO 2 in the Atlantic subpolar gyre (50-70 deg N, 60-10 deg W) during 1995-1997, we compare two methods of interpolation in space and time: a monthly distribution of surface pCO 2 constructed using multiple linear regressions on position and temperature, and a self-organizing neural network approach. Both methods confirm characteristics of the region found in previous work, i.e. the subpolar gyre is a sink for atmospheric CO 2 throughout the year, and exhibits a strong seasonal variability with the highest undersaturations occurring in spring and summer due to biological activity. As an annual average the surface pCO 2 is higher than estimates based on available syntheses of surface pCO 2 . This supports earlier suggestions that the sink of CO 2 in the Atlantic subpolar gyre has decreased over the last decade instead of increasing as previously assumed. The neural network is able to capture a more complex distribution than can be well represented by linear regressions, but both techniques agree relatively well on the average values of pCO 2 and derived fluxes. However, when both techniques are used with a subset of the data, the neural network predicts the remaining data to a much better accuracy than the regressions, with a residual standard deviation ranging from 3 to 11 μatm. The subpolar gyre is a net sink of CO 2 of 0.13 Gt-C/yr using the multiple linear regressions and 0.15 Gt-C/yr using the neural network, on average between 1995 and 1997. Both calculations were made with the NCEP monthly wind speeds converted to 10 m height and averaged between 1995 and 1997, and using the gas exchange coefficient of Wanninkhof

  20. Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds.

    Science.gov (United States)

    Ventura, Cristina; Latino, Diogo A R S; Martins, Filomena

    2013-01-01

    The performance of two QSAR methodologies, namely Multiple Linear Regressions (MLR) and Neural Networks (NN), towards the modeling and prediction of antitubercular activity was evaluated and compared. A data set of 173 potentially active compounds belonging to the hydrazide family and represented by 96 descriptors was analyzed. Models were built with Multiple Linear Regressions (MLR), single Feed-Forward Neural Networks (FFNNs), ensembles of FFNNs and Associative Neural Networks (AsNNs) using four different data sets and different types of descriptors. The predictive ability of the different techniques used were assessed and discussed on the basis of different validation criteria and results show in general a better performance of AsNNs in terms of learning ability and prediction of antitubercular behaviors when compared with all other methods. MLR have, however, the advantage of pinpointing the most relevant molecular characteristics responsible for the behavior of these compounds against Mycobacterium tuberculosis. The best results for the larger data set (94 compounds in training set and 18 in test set) were obtained with AsNNs using seven descriptors (R(2) of 0.874 and RMSE of 0.437 against R(2) of 0.845 and RMSE of 0.472 in MLRs, for test set). Counter-Propagation Neural Networks (CPNNs) were trained with the same data sets and descriptors. From the scrutiny of the weight levels in each CPNN and the information retrieved from MLRs, a rational design of potentially active compounds was attempted. Two new compounds were synthesized and tested against M. tuberculosis showing an activity close to that predicted by the majority of the models. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

  1. SPATKIN: a simulator for rule-based modeling of biomolecular site dynamics on surfaces.

    Science.gov (United States)

    Kochanczyk, Marek; Hlavacek, William S; Lipniacki, Tomasz

    2017-11-15

    Rule-based modeling is a powerful approach for studying biomolecular site dynamics. Here, we present SPATKIN, a general-purpose simulator for rule-based modeling in two spatial dimensions. The simulation algorithm is a lattice-based method that tracks Brownian motion of individual molecules and the stochastic firing of rule-defined reaction events. Because rules are used as event generators, the algorithm is network-free, meaning that it does not require to generate the complete reaction network implied by rules prior to simulation. In a simulation, each molecule (or complex of molecules) is taken to occupy a single lattice site that cannot be shared with another molecule (or complex). SPATKIN is capable of simulating a wide array of membrane-associated processes, including adsorption, desorption and crowding. Models are specified using an extension of the BioNetGen language, which allows to account for spatial features of the simulated process. The C ++ source code for SPATKIN is distributed freely under the terms of the GNU GPLv3 license. The source code can be compiled for execution on popular platforms (Windows, Mac and Linux). An installer for 64-bit Windows and a macOS app are available. The source code and precompiled binaries are available at the SPATKIN Web site (http://pmbm.ippt.pan.pl/software/spatkin). spatkin.simulator@gmail.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

  2. Exploiting Deep Neural Networks and Head Movements for Robust Binaural Localization of Multiple Sources in Reverberant Environments

    DEFF Research Database (Denmark)

    Ma, Ning; May, Tobias; Brown, Guy J.

    2017-01-01

    This paper presents a novel machine-hearing system that exploits deep neural networks (DNNs) and head movements for robust binaural localization of multiple sources in reverberant environments. DNNs are used to learn the relationship between the source azimuth and binaural cues, consisting...... of the complete cross-correlation function (CCF) and interaural level differences (ILDs). In contrast to many previous binaural hearing systems, the proposed approach is not restricted to localization of sound sources in the frontal hemifield. Due to the similarity of binaural cues in the frontal and rear...

  3. Global existence of periodic solutions in a simplified four-neuron BAM neural network model with multiple delays

    Directory of Open Access Journals (Sweden)

    2006-01-01

    Full Text Available We consider a simplified bidirectional associated memory (BAM neural network model with four neurons and multiple time delays. The global existence of periodic solutions bifurcating from Hopf bifurcations is investigated by applying the global Hopf bifurcation theorem due to Wu and Bendixson's criterion for high-dimensional ordinary differential equations due to Li and Muldowney. It is shown that the local Hopf bifurcation implies the global Hopf bifurcation after the second critical value of the sum of two delays. Numerical simulations supporting the theoretical analysis are also included.

  4. Assessment of the expected construction company’s net profit using neural network and multiple regression models

    Directory of Open Access Journals (Sweden)

    H.H. Mohamad

    2013-09-01

    This research aims to develop a mathematical model for assessing the expected net profit of any construction company. To achieve the research objective, four steps were performed. First, the main factors affecting firms’ net profit were identified. Second, pertinent data regarding the net profit factors were collected. Third, two different net profit models were developed using the Multiple Regression (MR and the Neural Network (NN techniques. The validity of the proposed models was also investigated. Finally, the results of both MR and NN models were compared to investigate the predictive capabilities of the two models.

  5. QSAR models for prediction study of HIV protease inhibitors using support vector machines, neural networks and multiple linear regression

    Directory of Open Access Journals (Sweden)

    Rachid Darnag

    2017-02-01

    Full Text Available Support vector machines (SVM represent one of the most promising Machine Learning (ML tools that can be applied to develop a predictive quantitative structure–activity relationship (QSAR models using molecular descriptors. Multiple linear regression (MLR and artificial neural networks (ANNs were also utilized to construct quantitative linear and non linear models to compare with the results obtained by SVM. The prediction results are in good agreement with the experimental value of HIV activity; also, the results reveal the superiority of the SVM over MLR and ANN model. The contribution of each descriptor to the structure–activity relationships was evaluated.

  6. Hybrid-Lambda: simulation of multiple merger and Kingman gene genealogies in species networks and species trees.

    Science.gov (United States)

    Zhu, Sha; Degnan, James H; Goldstien, Sharyn J; Eldon, Bjarki

    2015-09-15

    There has been increasing interest in coalescent models which admit multiple mergers of ancestral lineages; and to model hybridization and coalescence simultaneously. Hybrid-Lambda is a software package that simulates gene genealogies under multiple merger and Kingman's coalescent processes within species networks or species trees. Hybrid-Lambda allows different coalescent processes to be specified for different populations, and allows for time to be converted between generations and coalescent units, by specifying a population size for each population. In addition, Hybrid-Lambda can generate simulated datasets, assuming the infinitely many sites mutation model, and compute the F ST statistic. As an illustration, we apply Hybrid-Lambda to infer the time of subdivision of certain marine invertebrates under different coalescent processes. Hybrid-Lambda makes it possible to investigate biogeographic concordance among high fecundity species exhibiting skewed offspring distribution.

  7. Near-optimal power allocation with PSO algorithm for MIMO cognitive networks using multiple AF two-way relays

    KAUST Repository

    Alsharoa, Ahmad M.

    2014-06-01

    In this paper, the problem of power allocation for a multiple-input multiple-output two-way system is investigated in underlay Cognitive Radio (CR) set-up. In the CR underlay mode, secondary users are allowed to exploit the spectrum allocated to primary users in an opportunistic manner by respecting a tolerated temperature limit. The secondary networks employ an amplify-and-forward two-way relaying technique in order to maximize the sum rate under power budget and interference constraints. In this context, we formulate an optimization problem that is solved in two steps. First, we derive a closed-form expression of the optimal power allocated to terminals. Then, we employ a strong optimization tool based on particle swarm optimization algorithm to find the power allocated to secondary relays. Simulation results demonstrate the efficiency of the proposed solution and analyze the impact of some system parameters on the achieved performance. © 2014 IEEE.

  8. Dose controlled low energy electron irradiator for biomolecular films.

    Science.gov (United States)

    Kumar, S V K; Tare, Satej T; Upalekar, Yogesh V; Tsering, Thupten

    2016-03-01

    We have developed a multi target, Low Energy Electron (LEE), precise dose controlled irradiator for biomolecular films. Up to seven samples can be irradiated one after another at any preset electron energy and dose under UHV conditions without venting the chamber. In addition, one more sample goes through all the steps except irradiation, which can be used as control for comparison with the irradiated samples. All the samples are protected against stray electron irradiation by biasing them at -20 V during the entire period, except during irradiation. Ethernet based communication electronics hardware, LEE beam control electronics and computer interface were developed in house. The user Graphical User Interface to control the irradiation and dose measurement was developed using National Instruments Lab Windows CVI. The working and reliability of the dose controlled irradiator has been fully tested over the electron energy range of 0.5 to 500 eV by studying LEE induced single strand breaks to ΦX174 RF1 dsDNA.

  9. Spin valve sensor for biomolecular identification: Design, fabrication, and characterization

    Science.gov (United States)

    Li, Guanxiong

    Biomolecular identification, e.g., DNA recognition, has broad applications in biology and medicine such as gene expression analysis, disease diagnosis, and DNA fingerprinting. Therefore, we have been developing a magnetic biodetection technology based on giant magnetoresistive spin valve sensors and magnetic nanoparticle (developed for the magnetic nanoparticle detection, assuming the equivalent average field of magnetic nanoparticles and the coherent rotation of spin valve free layer magnetization. Micromagnetic simulations have also been performed for the spin valve sensors. The analytical model and micromagnetic simulations are found consistent with each other and are in good agreement with experiments. The prototype spin valve sensors have been fabricated at both micron and submicron scales. We demonstrated the detection of a single 2.8-mum magnetic microbead by micron-sized spin valve sensors. Based on polymer-mediated self-assembly and fine lithography, a bilayer lift-off process was developed to deposit magnetic nanoparticles onto the sensor surface in a controlled manner. With the lift-off deposition method, we have successfully demonstrated the room temperature detection of monodisperse 16-nm Fe3O 4 nanoparticles in a quantity from a few tens to several hundreds by submicron spin valve sensors, proving the feasibility of the nanoparticle detection. As desired for quantitative biodetection, a fairly linear dependence of sensor signal on the number of nanoparticles has been confirmed. The initial detection of DNA hybridization events labeled by magnetic nanoparticles further proved the magnetic biodetection concept.

  10. Dose controlled low energy electron irradiator for biomolecular films

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, S. V. K., E-mail: svkk@tifr.res.in; Tare, Satej T.; Upalekar, Yogesh V.; Tsering, Thupten [Tata Institute of Fundamental Research, Homi Bhabha Road, Colaba, Mumbai 400 005 (India)

    2016-03-15

    We have developed a multi target, Low Energy Electron (LEE), precise dose controlled irradiator for biomolecular films. Up to seven samples can be irradiated one after another at any preset electron energy and dose under UHV conditions without venting the chamber. In addition, one more sample goes through all the steps except irradiation, which can be used as control for comparison with the irradiated samples. All the samples are protected against stray electron irradiation by biasing them at −20 V during the entire period, except during irradiation. Ethernet based communication electronics hardware, LEE beam control electronics and computer interface were developed in house. The user Graphical User Interface to control the irradiation and dose measurement was developed using National Instruments Lab Windows CVI. The working and reliability of the dose controlled irradiator has been fully tested over the electron energy range of 0.5 to 500 eV by studying LEE induced single strand breaks to ΦX174 RF1 dsDNA.

  11. Modeling and Control of Heat Networks With Storage : The Single-Producer Multiple-Consumer Case

    NARCIS (Netherlands)

    Scholten, Tjardo; De Persis, Claudio; Tesi, Pietro

    In heat networks, energy storage in the form of hot water in a tank is a viable approach to balancing supply and demand. In order to store a desired amount of energy, both the volume and temperature of the water in the tank need to converge to desired setpoints. To this end, we provide a provably

  12. Dynamics of carbon dioxide transport in a multiple sink network (GHGT-11)

    NARCIS (Netherlands)

    Veltin, J.; Belfroid, S.P.C.

    2013-01-01

    As Carbon Capture and Storage slowly gets accepted and integrated as a mean for cleaner utilization of fossil fuels, the integration of capture, transport and storage becomes a key component to properly design a CO2 network. While the boundary conditions set by the capture and storage units have

  13. Bottom-up GGM algorithm for constructing multiple layered hierarchical gene regulatory networks

    Science.gov (United States)

    Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways. A bottom-up graphic Gaus...

  14. Intelligent Data Transfer for Multiple Sensor Networks over a Broad Temperature Range

    Science.gov (United States)

    Krasowski, Michael (Inventor)

    2018-01-01

    A sensor network may be configured to operate in extreme temperature environments. A sensor may be configured to generate a frequency carrier, and transmit the frequency carrier to a node. The node may be configured to amplitude modulate the frequency carrier, and transmit the amplitude modulated frequency carrier to a receiver.

  15. Modeling Multiple Human-Automation Distributed Systems using Network-form Games

    Science.gov (United States)

    Brat, Guillaume

    2012-01-01

    The paper describes at a high-level the network-form game framework (based on Bayes net and game theory), which can be used to model and analyze safety issues in large, distributed, mixed human-automation systems such as NextGen.

  16. Synthesis and optimization of steam system networks. 2. Multiple steam levels

    CSIR Research Space (South Africa)

    Price, T

    2010-08-01

    Full Text Available The use of steam in heat exchanger networks (HENs) can be reduced by the application of heat integration with the intention of debottlenecking the steam boiler and indirectly reducing the water requirement [Coetzee and Majozi. Ind. Eng. Chem. Res...

  17. Non-Orthogonal Multiple Access for Large-Scale 5G Networks: Interference Aware Design

    KAUST Repository

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

    2017-01-01

    the cell), which is a major performance limiting parameter in 5G networks. This article sheds light on the drastic negative-impact of intercell interference on the NOMA performance and advocates interference-aware NOMA design that jointly accounts for both

  18. A fast and efficient gene-network reconstruction method from multiple over-expression experiments

    Directory of Open Access Journals (Sweden)

    Thurner Stefan

    2009-08-01

    Full Text Available Abstract Background Reverse engineering of gene regulatory networks presents one of the big challenges in systems biology. Gene regulatory networks are usually inferred from a set of single-gene over-expressions and/or knockout experiments. Functional relationships between genes are retrieved either from the steady state gene expressions or from respective time series. Results We present a novel algorithm for gene network reconstruction on the basis of steady-state gene-chip data from over-expression experiments. The algorithm is based on a straight forward solution of a linear gene-dynamics equation, where experimental data is fed in as a first predictor for the solution. We compare the algorithm's performance with the NIR algorithm, both on the well known E. coli experimental data and on in-silico experiments. Conclusion We show superiority of the proposed algorithm in the number of correctly reconstructed links and discuss computational time and robustness. The proposed algorithm is not limited by combinatorial explosion problems and can be used in principle for large networks.

  19. A social and ecological assessment of tropical land uses at multiple scales: the Sustainable Amazon Network

    Science.gov (United States)

    Science has a critical role to play in guiding more sustainable development trajectories. Here we present the Sustainable Amazon Network (Rede Amazônia Sustentável, RAS): a multi-disciplinary research initiative involving more than 30 partner organisations working to assess both ...

  20. Pulse patterning effect in optical pulse division multiplexing for flexible single wavelength multiple access optical network

    Science.gov (United States)

    Jung, Sun-Young; Kim, Chang-Hun; Han, Sang-Kook

    2018-05-01

    A demand for high spectral efficiency requires multiple access within a single wavelength, but the uplink signals are significantly degraded because of optical beat interference (OBI) in intensity modulation/direct detection system. An optical pulse division multiplexing (OPDM) technique was proposed that could effectively reduce the OBI via a simple method as long as near-orthogonality is satisfied, but the condition was strict, and thus, the number of multiplexing units was very limited. We propose pulse pattern enhanced OPDM (e-OPDM) to reduce the OBI and improve the flexibility in multiple access within a single wavelength. The performance of the e-OPDM and patterning effect are experimentally verified after 23-km single mode fiber transmission. By employing pulse patterning in OPDM, the tight requirement was relaxed by extending the optical delay dynamic range. This could support more number of access with reduced OBI, which could eventually enhance a multiple access function.

  1. On using multiple routing metrics with destination sequenced distance vector protocol for MultiHop wireless ad hoc networks

    Science.gov (United States)

    Mehic, M.; Fazio, P.; Voznak, M.; Partila, P.; Komosny, D.; Tovarek, J.; Chmelikova, Z.

    2016-05-01

    A mobile ad hoc network is a collection of mobile nodes which communicate without a fixed backbone or centralized infrastructure. Due to the frequent mobility of nodes, routes connecting two distant nodes may change. Therefore, it is not possible to establish a priori fixed paths for message delivery through the network. Because of its importance, routing is the most studied problem in mobile ad hoc networks. In addition, if the Quality of Service (QoS) is demanded, one must guarantee the QoS not only over a single hop but over an entire wireless multi-hop path which may not be a trivial task. In turns, this requires the propagation of QoS information within the network. The key to the support of QoS reporting is QoS routing, which provides path QoS information at each source. To support QoS for real-time traffic one needs to know not only minimum delay on the path to the destination but also the bandwidth available on it. Therefore, throughput, end-to-end delay, and routing overhead are traditional performance metrics used to evaluate the performance of routing protocol. To obtain additional information about the link, most of quality-link metrics are based on calculation of the lost probabilities of links by broadcasting probe packets. In this paper, we address the problem of including multiple routing metrics in existing routing packets that are broadcasted through the network. We evaluate the efficiency of such approach with modified version of DSDV routing protocols in ns-3 simulator.

  2. Applications of atomic force microscopy to the studies of biomaterials in biomolecular systems

    Science.gov (United States)

    Ma, Xiang

    Atomic force microscopy (AFM) is a unique tool for the studies of nanoscale structures and interactions. In this dissertation, I applied AFM to study transitions among multiple states of biomaterials in three different microscopic biomolecular systems: MukB-dependent DNA condensation, holdfast adhesion, and virus elasticity. To elucidate the mechanism of MukB-dependent DNA condensation, I have studied the conformational changes of MukB proteins as indicators for the strength of interactions between MukB, DNA and other molecular factors, such as magnesium and ParC proteins, using high-resolution AFM imaging. To determine the physical origins of holdfast adhesion, I have investigated the dynamics of adhesive force development of the holdfast, employing AFM force spectroscopy. By measuring rupture forces between the holdfast and the substrate, I showed that the holdfast adhesion is strongly time-dependent and involves transformations at multiple time scales. Understanding the mechanisms of adhesion force development of the holdfast will be critical for future engineering of holdfasts properties for various applications. Finally, I have examined the elasticity of self-assembled hepatitis B virus-like particles (HBV VLPs) and brome mosaic virus (BMV) in response to changes of pH and salinity, using AFM nanoindentation. The distributions of elasticity were mapped on a single particle level and compared between empty, RNA- and gold-filled HBV VLPs. I found that a single HBV VLP showed heterogeneous distribution of elasticity and a two-step buckling transition, suggesting a discrete property of HBV capsids. For BMV, I have showed that viruses containing different RNA molecules can be distinguished by mechanical measurements, while they are indistinguishable by morphology. I also studied the effect of pH on the elastic behaviors of three-particle BMV and R3/4 BMV. This study can yield insights into RNA presentation/release mechanisms, and could help us to design novel drug

  3. Lewis Research Center studies of multiple large wind turbine generators on a utility network

    Science.gov (United States)

    Gilbert, L. J.; Triezenberg, D. M.

    1979-01-01

    A NASA-Lewis program to study the anticipated performance of a wind turbine generator farm on an electric utility network is surveyed. The paper describes the approach of the Lewis Wind Energy Project Office to developing analysis capabilities in the area of wind turbine generator-utility network computer simulations. Attention is given to areas such as, the Lewis Purdue hybrid simulation, an independent stability study, DOE multiunit plant study, and the WEST simulator. Also covered are the Lewis mod-2 simulation including analog simulation of a two wind turbine system and comparison with Boeing simulation results, and gust response of a two machine model. Finally future work to be done is noted and it is concluded that the study shows little interaction between the generators and between the generators and the bus.

  4. Multiple Linear Regression Model Based on Neural Network and Its Application in the MBR Simulation

    Directory of Open Access Journals (Sweden)

    Chunqing Li

    2012-01-01

    Full Text Available The computer simulation of the membrane bioreactor MBR has become the research focus of the MBR simulation. In order to compensate for the defects, for example, long test period, high cost, invisible equipment seal, and so forth, on the basis of conducting in-depth study of the mathematical model of the MBR, combining with neural network theory, this paper proposed a three-dimensional simulation system for MBR wastewater treatment, with fast speed, high efficiency, and good visualization. The system is researched and developed with the hybrid programming of VC++ programming language and OpenGL, with a multifactor linear regression model of affecting MBR membrane fluxes based on neural network, applying modeling method of integer instead of float and quad tree recursion. The experiments show that the three-dimensional simulation system, using the above models and methods, has the inspiration and reference for the future research and application of the MBR simulation technology.

  5. Efficient Steplike Carrier Multiplication in Percolative Networks of Epitaxially Connected PbSe Nanocrystals

    NARCIS (Netherlands)

    Kulkarni, A.; Evers, W.H.; Tomić, Stanko; Beard, Matthew C.; Vanmaekelbergh, Daniel; Siebbeles, L.D.A.

    2018-01-01

    Carrier multiplication (CM) is a process in which a single photon excites two or more electrons. CM is of interest to enhance the efficiency of a solar cell. Until now, CM in thin films and solar cells of semiconductor nanocrystals (NCs) has been found at photon energies well above the minimum

  6. Cognitive Multiple-Antenna Network with Outage and Rate Margins at the Primary System

    DEFF Research Database (Denmark)

    Maham, Behrouz; Popovski, Petar

    2015-01-01

    In the common model for spectrum sharing, cognitive users can access the spectrum as long as the target performance in the legitimate primary system is not violated. In this paper, we consider a downlink primary multiple-inputsingle- output (MISO) system which operates under a controlled interfer...

  7. Fault diagnosis of sensor networked structures with multiple faults using a virtual beam based approach

    Science.gov (United States)

    Wang, H.; Jing, X. J.

    2017-07-01

    This paper presents a virtual beam based approach suitable for conducting diagnosis of multiple faults in complex structures with limited prior knowledge of the faults involved. The "virtual beam", a recently-proposed concept for fault detection in complex structures, is applied, which consists of a chain of sensors representing a vibration energy transmission path embedded in the complex structure. Statistical tests and adaptive threshold are particularly adopted for fault detection due to limited prior knowledge of normal operational conditions and fault conditions. To isolate the multiple faults within a specific structure or substructure of a more complex one, a 'biased running' strategy is developed and embedded within the bacterial-based optimization method to construct effective virtual beams and thus to improve the accuracy of localization. The proposed method is easy and efficient to implement for multiple fault localization with limited prior knowledge of normal conditions and faults. With extensive experimental results, it is validated that the proposed method can localize both single fault and multiple faults more effectively than the classical trust index subtract on negative add on positive (TI-SNAP) method.

  8. What do you mean "drunk"? Convergent validation of multiple methods of mapping alcohol expectancy memory networks.

    Science.gov (United States)

    Reich, Richard R; Ariel, Idan; Darkes, Jack; Goldman, Mark S

    2012-09-01

    The configuration and activation of memory networks have been theorized as mechanisms that underlie the often observed link between alcohol expectancies and drinking. A key component of this network is the expectancy "drunk." The memory network configuration of "drunk" was mapped by using cluster analysis of data gathered from the paired-similarities task (PST) and the Alcohol Expectancy Multi-Axial Assessment (AEMAX). A third task, the free associates task (FA), assessed participants' strongest alcohol expectancy associates and was used as a validity check for the cluster analyses. Six hundred forty-seven 18-19-year-olds completed these measures and a measure of alcohol consumption at baseline assessment for a 5-year longitudinal study. For both the PST and AEMAX, "drunk" clustered with mainly negative and sedating effects (e.g., "sick," "dizzy," "sleepy") in lighter drinkers and with more positive and arousing effects (e.g., "happy," "horny," "outgoing") in heavier drinkers, showing that the cognitive organization of expectancies reflected drinker type (and might influence the choice to drink). Consistent with the cluster analyses, in participants who gave "drunk" as an FA response, heavier drinkers rated the word as more positive and arousing than lighter drinkers. Additionally, gender did not account for the observed drinker-type differences. These results support the notion that for some emerging adults, drinking may be linked to what they mean by the word "drunk." PsycINFO Database Record (c) 2012 APA, all rights reserved.

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

    Science.gov (United States)

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

    2018-01-06

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

  10. The impact of multiple information on coupled awareness-epidemic dynamics in multiplex networks

    Science.gov (United States)

    Pan, Yaohui; Yan, Zhijun

    2018-02-01

    Growing interest has emerged in the study of the interplay between awareness and epidemics in multiplex networks. However, previous studies on this issue usually assume that all aware individuals take the same level of precautions, ignoring individual heterogeneity. In this paper, we investigate the coupled awareness-epidemic dynamics in multiplex networks considering individual heterogeneity. Here, the precaution levels are heterogeneous and depend on three types of information: contact information and local and global prevalence information. The results show that contact-based precautions can decrease the epidemic prevalence and augment the epidemic threshold, but prevalence-based precautions, regardless of local or global information, can only decrease the epidemic prevalence. Moreover, unlike previous studies in single-layer networks, we do not find a greater impact of local prevalence information on the epidemic prevalence compared to global prevalence information. In addition, we find that the altruistic behaviors of infected individuals can effectively suppress epidemic spreading, especially when the level of contact-based precaution is high.

  11. Structural health monitoring and damage assessment using measured FRFs from multiple sensors. Part II. Decision making with RBF networks

    Energy Technology Data Exchange (ETDEWEB)

    Zang, C.; Friswell, M.I. [Dept. of Aerospace Engineering, Univ. of Bristol, Bristol (United Kingdom); Imregun, M. [Dept. of Mechanical Engineering, Imperial Coll., London (United Kingdom)

    2003-07-01

    This paper is the second of two papers concerned with structural health monitoring and damage assessment using measured FRFs from multiple sensors, and discusses the decision making technique with radial basis function (RBF) neural networks. In PART 1 of the paper, the correlation criteria showed their capability to indicate various changes to the structure's state. PART 2, presented here, develops the methodology of decision theory to identify precisely all of the structure states. Although, the statistical approach can be used for classification, interpreting the information is difficult. Neural network techniques have been proven to possess many advantages for classification due to their learning ability and good generalization. In this paper, the radial basis function neural network is applied for function approximation and recognition. The key idea is to partition the input space (the indicators of the correlation criteria) into a number of subspaces that are in the form of hyper spheres. Then, the widely used k-mean clustering algorithm was selected as a logical approach to detecting the structure states. A bookshelf structure with measured frequency responses from 24 accelerometers was used to demonstrate the effectiveness of the method. The results show the successful classification of all structure states, for instance, the undamaged and damage states, damage locations and damage levels, and the environmental variability. (orig.)

  12. Effectiveness of multiple therapeutic strategies in neovascular glaucoma patients: A PRISMA-compliant network meta-analysis.

    Science.gov (United States)

    Dong, Zixian; Gong, Jianyang; Liao, Rongfeng; Xu, Shaojun

    2018-04-01

    Neovascular glaucoma (NVG) is a severe secondary glaucoma with uncontrolled intraocular pressure that leads to serious eye pain and vision loss. Presently, the therapeutic strategies for NVG are diverse, but the therapeutic effects are still not ideal. We performed a network analysis to assess the effect of multiple therapeutic strategies on the treatment of NVG patients. We searched public electronic databases through April 2017 using the following keywords "neovascular glaucoma," "iris neovascularization," "hemorrhagic glaucoma," and "random" without language restrictions. The outcome considered in the present analysis was treatment success rate. A network meta-analysis and multilevel mixed-effects logistic regression were used to compare regimens. We included 27 articles assessing a total of 1884 NVG patients in our analysis. According to the network analysis, interferon and mitomycin plus trabeculectomy (94.9%), glaucoma valve implantation (86.9%), and iris photocoagulation plus trabeculectomy (81.9%) were the most likely to improve treatment success rate in NVG patients. The multilevel logistic regression analysis showed that glaucoma valve, bevacizumab, interferon, cyclophotocoagulation, trabeculectomy, iris photocoagulation, ranibizumab, and mitomycin had advantages in terms of improving treatment success rate in NVG patients. However, the application of retinal photocoagulation and vitrectomy reduced patient treatment success rate. The regimen including mitomycin, interferon, and trabeculectomy was the most likely to improve the treatment success rate in NVG patients. The application of glaucoma valve and bevacizumab were more beneficial for improving patient treatment success rate as a surgery and as an agent, respectively.

  13. Phylogeny and evolutionary histories of Pyrus L. revealed by phylogenetic trees and networks based on data from multiple DNA sequences.

    Science.gov (United States)

    Zheng, Xiaoyan; Cai, Danying; Potter, Daniel; Postman, Joseph; Liu, Jing; Teng, Yuanwen

    2014-11-01

    Reconstructing the phylogeny of Pyrus has been difficult due to the wide distribution of the genus and lack of informative data. In this study, we collected 110 accessions representing 25 Pyrus species and constructed both phylogenetic trees and phylogenetic networks based on multiple DNA sequence datasets. Phylogenetic trees based on both cpDNA and nuclear LFY2int2-N (LN) data resulted in poor resolution, especially, only five primary species were monophyletic in the LN tree. A phylogenetic network of LN suggested that reticulation caused by hybridization is one of the major evolutionary processes for Pyrus species. Polytomies of the gene trees and star-like structure of cpDNA networks suggested rapid radiation is another major evolutionary process, especially for the occidental species. Pyrus calleryana and P. regelii were the earliest diverged Pyrus species. Two North African species, P. cordata, P. spinosa and P. betulaefolia were descendent of primitive stock Pyrus species and still share some common molecular characters. Southwestern China, where a large number of P. pashia populations are found, is probably the most important diversification center of Pyrus. More accessions and nuclear genes are needed for further understanding the evolutionary histories of Pyrus. Copyright © 2014 Elsevier Inc. All rights reserved.

  14. Multiple Sensing Application on Wireless Sensor Network Simulation using NS3

    Science.gov (United States)

    Kurniawan, I. F.; Bisma, R.

    2018-01-01

    Hardware enhancement provides opportunity to install various sensor device on single monitoring node which then enables users to acquire multiple data simultaneously. Constructing multiple sensing application in NS3 is a challenging task since numbers of aspects such as wireless communication, packet transmission pattern, and energy model must be taken into account. Despite of numerous types of monitoring data available, this study only considers two types such as periodic, and event-based data. Periodical data will generate monitoring data follows configured interval, while event-based transmit data when certain determined condition is met. Therefore, this study attempts to cover mentioned aspects in NS3. Several simulations are performed with different number of nodes on arbitrary communication scheme.

  15. Code division multiple-access techniques in optical fiber networks. II - Systems performance analysis

    Science.gov (United States)

    Salehi, Jawad A.; Brackett, Charles A.

    1989-08-01

    A technique based on optical orthogonal codes was presented by Salehi (1989) to establish a fiber-optic code-division multiple-access (FO-CDMA) communications system. The results are used to derive the bit error rate of the proposed FO-CDMA system as a function of data rate, code length, code weight, number of users, and receiver threshold. The performance characteristics for a variety of system parameters are discussed. A means of reducing the effective multiple-access interference signal by placing an optical hard-limiter at the front end of the desired optical correlator is presented. Performance calculations are shown for the FO-CDMA with an ideal optical hard-limiter, and it is shown that using a optical hard-limiter would, in general, improve system performance.

  16. Determination of the hexagonal network parameters of the quartz β using neutron multiple diffraction

    International Nuclear Information System (INIS)

    Campos, L.C.; Parente, C.B.R.; Mazzocchi, V.L.; Helene, O.

    2000-01-01

    In this work, neutron multiple diffraction is employed for the determination of the parameters a and c of the β-quartz hexagonal cell. This crystalline phase of silica (SiO 2 ) occurs in temperatures between ca. 846 and 1143 K. A β-quartz neutron multiple diffraction pattern has been used in the determinations. This pattern was obtained with a natural quartz single crystal heated to 1003 K. During the indexing of the pattern it was verified that most of the pairs of secondary reflections, which are responsible for the formation of peaks, could be classified as 'good for the determination of a' or 'good for the determination of c'. With this classification, it became possible to employ an iterative method for the determination of both parameters. After 8 cycles of iteration the values found for the parameters were a = 4.9964 +- 0.0018 and c = 5.46268 +- 0.00052 A. (author)

  17. Biomolecular detection using a metal semiconductor field effect transistor

    Science.gov (United States)

    Estephan, Elias; Saab, Marie-Belle; Buzatu, Petre; Aulombard, Roger; Cuisinier, Frédéric J. G.; Gergely, Csilla; Cloitre, Thierry

    2010-04-01

    In this work, our attention was drawn towards developing affinity-based electrical biosensors, using a MESFET (Metal Semiconductor Field Effect Transistor). Semiconductor (SC) surfaces must be prepared before the incubations with biomolecules. The peptides route was adapted to exceed and bypass the limits revealed by other types of surface modification due to the unwanted unspecific interactions. As these peptides reveal specific recognition of materials, then controlled functionalization can be achieved. Peptides were produced by phage display technology using a library of M13 bacteriophage. After several rounds of bio-panning, the phages presenting affinities for GaAs SC were isolated; the DNA of these specific phages were sequenced, and the peptide with the highest affinity was synthesized and biotinylated. To explore the possibility of electrical detection, the MESFET fabricated with the GaAs SC were used to detect the streptavidin via the biotinylated peptide in the presence of the bovine Serum Albumin. After each surface modification step, the IDS (current between the drain and the source) of the transistor was measured and a decrease in the intensity was detected. Furthermore, fluorescent microscopy was used in order to prove the specificity of this peptide and the specific localisation of biomolecules. In conclusion, the feasibility of producing an electrical biosensor using a MESFET has been demonstrated. Controlled placement, specific localization and detection of biomolecules on a MESFET transistor were achieved without covering the drain and the source. This method of functionalization and detection can be of great utility for biosensing application opening a new way for developing bioFETs (Biomolecular Field-Effect Transistor).

  18. Evolution of biomolecular loadings along a major river system

    Science.gov (United States)

    Freymond, Chantal V.; Kündig, Nicole; Stark, Courcelle; Peterse, Francien; Buggle, Björn; Lupker, Maarten; Plötze, Michael; Blattmann, Thomas M.; Filip, Florin; Giosan, Liviu; Eglinton, Timothy I.

    2018-02-01

    Understanding the transport history and fate of organic carbon (OC) within river systems is crucial in order to constrain the dynamics and significance of land-ocean interactions as a component of the global carbon cycle. Fluvial export and burial of terrestrial OC in marine sediments influences atmospheric CO2 over a range of timescales, while river-dominated sedimentary sequences can provide valuable archives of paleoenvironmental information. While there is abundant evidence that the association of organic matter (OM) with minerals exerts an important influence on its stability as well as hydrodynamic behavior in aquatic systems, there is a paucity of information on where such associations form and how they evolve during fluvial transport. Here, we track total organic carbon (TOC) and terrestrial biomarker concentrations (plant wax-derived long-chain fatty acids (FA), branched glycerol dialkyl glycerol tetraethers (brGDGTs) and lignin-derived phenols) in sediments collected along the entire course of the Danube River system in the context of sedimentological parameters. Mineral-specific surface area-normalized biomarker and TOC concentrations show a systematic decrease from the upper to the lower Danube basin. Changes in OM loading of the available mineral phase correspond to a net decrease of 70-80% of different biomolecular components. Ranges for biomarker loadings on Danube River sediments, corresponding to 0.4-1.5 μgFA/m2 for long-chain (n-C24-32) fatty acids and 17-71 ngbrGDGT/m2 for brGDGTs, are proposed as a benchmark for comparison with other systems. We propose that normalizing TOC as well as biomarker concentrations to mineral surface area provides valuable quantitative constraints on OM dynamics and organo-mineral interactions during fluvial transport from terrigenous source to oceanic sink.

  19. Soft Supercharging of Biomolecular Ions in Electrospray Ionization Mass Spectrometry

    Science.gov (United States)

    Chingin, Konstantin; Xu, Ning; Chen, Huanwen

    2014-06-01

    The charge states of biomolecular ions in ESI-MS can be significantly increased by the addition of low-vapor supercharging (SC) reagents into the spraying solution. Despite the considerable interest from the community, the mechanistic aspects of SC are not well understood and are hotly debated. Arguments that denaturation accounts for the increased charging observed in proteins sprayed from aqueous solutions containing SC reagent have been published widely, but often with incomplete or ambiguous supporting data. In this work, we explored ESI MS charging and SC behavior of several biopolymers including proteins and DNA oligonucleotides. Analytes were ionized from 100 mM ammonium acetate (NH4Ac) aqueous buffer in both positive (ESI+) and negative (ESI-) ion modes. SC was induced either with m-NBA or by the elevated temperature of ESI capillary. For all the analytes studied we, found striking differences in the ESI MS response to these two modes of activation. The data suggest that activation with m-NBA results in more extensive analyte charging with lower degree of denaturation. When working solution with m-NBA was analyzed at elevated temperatures, the SC effect from m-NBA was neutralized. Instead, the net SC effect was similar to the SC effect achieved by thermal activation only. Overall, our observations indicate that SC reagents enhance ESI charging of biomolecules via distinctly different mechanism compared with the traditional approaches based on analyte denaturation. Instead, the data support the hypothesis that the SC phenomenon involves a direct interaction between a biopolymer and SC reagent occurring in evaporating ESI droplets.

  20. Polarization diversity scheme on spectral polarization coding optical code-division multiple-access network

    Science.gov (United States)

    Yen, Chih-Ta; Huang, Jen-Fa; Chang, Yao-Tang; Chen, Bo-Hau

    2010-12-01

    We present an experiment demonstrating the spectral-polarization coding optical code-division multiple-access system introduced with a nonideal state of polarization (SOP) matching conditions. In the proposed system, the encoding and double balanced-detection processes are implemented using a polarization-diversity scheme. Because of the quasiorthogonality of Hadamard codes combining with array waveguide grating routers and a polarization beam splitter, the proposed codec pair can encode-decode multiple code words of Hadamard code while retaining the ability for multiple-access interference cancellation. The experimental results demonstrate that when the system is maintained with an orthogonal SOP for each user, an effective reduction in the phase-induced intensity noise is obtained. The analytical SNR values are found to overstate the experimental results by around 2 dB when the received effective power is large. This is mainly limited by insertion losses of components and a nonflattened optical light source. Furthermore, the matching conditions can be improved by decreasing nonideal influences.

  1. Development of an informatics infrastructure for data exchange of biomolecular simulations: Architecture, data models and ontology.

    Science.gov (United States)

    Thibault, J C; Roe, D R; Eilbeck, K; Cheatham, T E; Facelli, J C

    2015-01-01

    Biomolecular simulations aim to simulate structure, dynamics, interactions, and energetics of complex biomolecular systems. With the recent advances in hardware, it is now possible to use more complex and accurate models, but also reach time scales that are biologically significant. Molecular simulations have become a standard tool for toxicology and pharmacology research, but organizing and sharing data - both within the same organization and among different ones - remains a substantial challenge. In this paper we review our recent work leading to the development of a comprehensive informatics infrastructure to facilitate the organization and exchange of biomolecular simulations data. Our efforts include the design of data models and dictionary tools that allow the standardization of the metadata used to describe the biomedical simulations, the development of a thesaurus and ontology for computational reasoning when searching for biomolecular simulations in distributed environments, and the development of systems based on these models to manage and share the data at a large scale (iBIOMES), and within smaller groups of researchers at laboratory scale (iBIOMES Lite), that take advantage of the standardization of the meta data used to describe biomolecular simulations.

  2. On the effectiveness of single and multiple base station sleep modes in cellular networks

    OpenAIRE

    Marsan, Marco Ajmone; Chiaraviglio, Luca; Ciullo, Delia; Meo, Michela

    2013-01-01

    In this paper we study base station sleep modes that, by reducing power consumption in periods of low traffic, improve the energy efficiency of cellular access networks. We assume that when some base stations enter sleep mode, radio coverage and service provisioning are provided by the base stations that remain active, so as to guarantee that service is available over the whole area at all times. This may be an optimistic assumption in the case of the sparse base station layouts typical of ru...

  3. The performance of integrated health care networks in continuity of care: a qualitative multiple case study of COPD patients

    Directory of Open Access Journals (Sweden)

    Sina Waibel

    2015-07-01

    Full Text Available Background: Integrated health care networks (IHN are promoted in numerous countries as a response to fragmented care delivery by providing a coordinated continuum of services to a defined population. However, evidence on their effectiveness and outcome is scarce, particularly considering continuity across levels of care; that is the patient's experience of connected and coherent care received from professionals of the different care levels over time. The objective was to analyse the chronic obstructive pulmonary disease (COPD patients’ perceptions of continuity of clinical management and information across care levels and continuity of relation in IHN of the public health care system of Catalonia.Methods: A qualitative multiple case study was conducted, where the cases are COPD patients. A theoretical sample was selected in two stages: (1 study contexts: IHN and (2 study cases consisting of COPD patients. Data were collected by means of individual, semi-structured interviews to the patients, their general practitioners and pulmonologists and review of records. A thematic content analysis segmented by IHN and cases with a triangulation of sources and analysists was carried out.Results: COPD patients of all networks perceived that continuity of clinical management was existent due to clear distribution of roles for COPD care across levels, rapid access to care during exacerbations and referrals to secondary care when needed; nevertheless, patients of some networks highlighted too long waiting times to non-urgent secondary care. Physicians generally agreed with patients, however, also indicated unclear distribution of roles, some inadequate referrals and long waiting times to primary care in some networks. Concerning continuity of information, patients across networks considered that their clinical information was transferred across levels via computer and that physicians also used informal communication mechanisms (e-mail, telephone; whereas

  4. Reliability assessment of a multistate freight network for perishable merchandise with multiple suppliers and buyers

    Science.gov (United States)

    Lin, Yi-Kuei; Yeh, Cheng-Ta; Huang, Cheng-Fu

    2017-01-01

    This study develops a multistate freight network for single and perishable merchandise to assess the freight performance, where a node denotes a supplier, a distribution centre, or a buyer, while a logistics company providing a freight traffic service is denoted by an edge. For each logistics company, carrying capacity should be multistate since partial capacity may be reserved by some customers. The merchandise may perish or be perished during conveyance because of disadvantageous weather or collision in carrying such that the number of intact cargoes may be insufficient for the buyers. Hence, according to the perspective of supply chain management, the reliability, a probability of the network to successfully deliver the cargoes from the suppliers to the buyers subject to a budget, is proposed to be a performance index, where the suppliers and buyers are not the previous customers. An algorithm in terms of minimal paths to assess the reliability is developed. A fruit logistics case is adopted to explore the managerial implications of the reliability using sensitivity analysis.

  5. A Multiple-Reception Access Protocol with Interruptions with Mixed Priorities in CDMA Networks

    Institute of Scientific and Technical Information of China (English)

    Lu Xiaowen; Zhu Jinkang

    2003-01-01

    A novel access protocol called Multiple-Reception Access Protocol (MRAP) and its modification MRAP/WI are proposed. In this protocol, all colliding users with a common code can be identified by the base station due to the offset of arrival time Thus they can retransmit access requests under the base station's control. Furthermore new arrivals with higher priority level can interrupt the lower retransmission in order to reduce its access delay although it increases the lower priority's delay. Simulation results of MRAP and MRAP/WI are given in order to highlight the superior performance of the proposed approach.

  6. Zwitterionic Silane Copolymer for Ultra-Stable and Bright Biomolecular Probes Based on Fluorescent Quantum Dot Nanoclusters.

    Science.gov (United States)

    Dembele, Fatimata; Tasso, Mariana; Trapiella-Alfonso, Laura; Xu, Xiangzhen; Hanafi, Mohamed; Lequeux, Nicolas; Pons, Thomas

    2017-05-31

    Fluorescent semiconductor quantum dots (QDs) exhibit several unique properties that make them suitable candidates for biomolecular sensing, including high brightness, photostability, broad excitation, and narrow emission spectra. Assembling these QDs into robust and functionalizable nanosized clusters (QD-NSCs) can provide fluorescent probes that are several orders of magnitude brighter than individual QDs, thus allowing an even greater sensitivity of detection with simplified instrumentation. However, the formation of compact, antifouling, functionalizable, and stable QD-NSCs remains a challenging task, especially for a use at ultralow concentrations for single-molecule detection. Here, we describe the development of fluorescent QD-NSCs envisioned as a tool for fast and sensitive biomolecular recognition. First, QDs were assembled into very compact 100-150 nm diameter spherical aggregates; the final QD-NSCs were obtained by growing a cross-linked silica shell around these aggregates. Hydrolytic stability in several concentration and pH conditions is a key requirement for a potential and efficient single-molecule detection tool. However, the hydrolysis of Si-O-Si bonds leads to desorption of monosilane-based surface groups at very low silica concentrations or in a slightly basic medium. Thus, we designed a novel multidentate copolymer composed of multiple silane as well as zwitterionic monomers. Coating silica beads with this multidentate copolymer provided a robust surface chemistry that was demonstrated to be stable against hydrolysis, even at low concentrations. Copolymer-coated silica beads also showed low fouling properties and high colloidal stability in saline solutions. Furthermore, incorporation of additional azido-monomers enabled easy functionalization of QD-NSCs using copper-free bio-orthogonal cyclooctyne-azide click chemistry, as demonstrated by a biotin-streptavidin affinity test.

  7. Allosteric transitions of supramolecular systems explored by network models: application to chaperonin GroEL.

    Directory of Open Access Journals (Sweden)

    Zheng Yang

    2009-04-01

    Full Text Available Identification of pathways involved in the structural transitions of biomolecular systems is often complicated by the transient nature of the conformations visited across energy barriers and the multiplicity of paths accessible in the multidimensional energy landscape. This task becomes even more challenging in exploring molecular systems on the order of megadaltons. Coarse-grained models that lend themselves to analytical solutions appear to be the only possible means of approaching such cases. Motivated by the utility of elastic network models for describing the collective dynamics of biomolecular systems and by the growing theoretical and experimental evidence in support of the intrinsic accessibility of functional substates, we introduce a new method, adaptive anisotropic network model (aANM, for exploring functional transitions. Application to bacterial chaperonin GroEL and comparisons with experimental data, results from action minimization algorithm, and previous simulations support the utility of aANM as a computationally efficient, yet physically plausible, tool for unraveling potential transition pathways sampled by large complexes/assemblies. An important outcome is the assessment of the critical inter-residue interactions formed/broken near the transition state(s, most of which involve conserved residues.

  8. Multiple-mode reconfigurable electro-optic switching network for optical fiber sensor array

    Science.gov (United States)

    Chen, Ray T.; Wang, Michael R.; Jannson, Tomasz; Baumbick, Robert

    1991-01-01

    This paper reports the first switching network compatible with multimode fibers. A one-to-many cascaded reconfigurable interconnection was built. A thin glass substrate was used as the guiding medium which provides not only higher coupling efficiency from multimode fiber to waveguide but also better tolerance of phase-matching conditions. Involvement of a total-internal-reflection hologram and multimode waveguide eliminates interface problems between fibers and waveguides. The DCG polymer graft has proven to be reliable from -180 C to +200 C. Survivability of such an electrooptic system in harsh environments is further ensured. LiNbO3 was chosen as the E-O material because of its stability at high temperatures (phase-transition temperature of more than 1000 C) and maturity of E-O device technology. Further theoretical calculation was conducted to provide the optimal interaction length and device capacitance.

  9. The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature.

    Science.gov (United States)

    Özgür, Arzucan; Hur, Junguk; He, Yongqun

    2016-01-01

    The Interaction Network Ontology (INO) logically represents biological interactions, pathways, and networks. INO has been demonstrated to be valuable in providing a set of structured ontological terms and associated keywords to support literature mining of gene-gene interactions from biomedical literature. However, previous work using INO focused on single keyword matching, while many interactions are represented with two or more interaction keywords used in combination. This paper reports our extension of INO to include combinatory patterns of two or more literature mining keywords co-existing in one sentence to represent specific INO interaction classes. Such keyword combinations and related INO interaction type information could be automatically obtained via SPARQL queries, formatted in Excel format, and used in an INO-supported SciMiner, an in-house literature mining program. We studied the gene interaction sentences from the commonly used benchmark Learning Logic in Language (LLL) dataset and one internally generated vaccine-related dataset to identify and analyze interaction types containing multiple keywords. Patterns obtained from the dependency parse trees of the sentences were used to identify the interaction keywords that are related to each other and collectively represent an interaction type. The INO ontology currently has 575 terms including 202 terms under the interaction branch. The relations between the INO interaction types and associated keywords are represented using the INO annotation relations: 'has literature mining keywords' and 'has keyword dependency pattern'. The keyword dependency patterns were generated via running the Stanford Parser to obtain dependency relation types. Out of the 107 interactions in the LLL dataset represented with two-keyword interaction types, 86 were identified by using the direct dependency relations. The LLL dataset contained 34 gene regulation interaction types, each of which associated with multiple keywords. A

  10. Performance analysis of two-way amplify and forward relaying with adaptive modulation over multiple relay network

    KAUST Repository

    Hwang, Kyusung

    2011-02-01

    In this letter, we propose two-way amplify-and-forward relaying in conjunction with adaptive modulation in order to improve spectral efficiency of relayed communication systems while monitoring the required error performance. We also consider a multiple relay network where only the best relay node is utilized so that the diversity order increases while maintaining a low complexity of implementation as the number of relays increases. Based on the best relay selection criterion, we offer an upper bound on the signal-to-noise ratio to keep the performance analysis tractable. Our numerical examples show that the proposed system offers a considerable gain in spectral efficiency while satisfying the error rate requirements. © 2011 IEEE.

  11. Time Series Analysis of Soil Radon Data Using Multiple Linear Regression and Artificial Neural Network in Seismic Precursory Studies

    Science.gov (United States)

    Singh, S.; Jaishi, H. P.; Tiwari, R. P.; Tiwari, R. C.

    2017-07-01

    This paper reports the analysis of soil radon data recorded in the seismic zone-V, located in the northeastern part of India (latitude 23.73N, longitude 92.73E). Continuous measurements of soil-gas emission along Chite fault in Mizoram (India) were carried out with the replacement of solid-state nuclear track detectors at weekly interval. The present study was done for the period from March 2013 to May 2015 using LR-115 Type II detectors, manufactured by Kodak Pathe, France. In order to reduce the influence of meteorological parameters, statistical analysis tools such as multiple linear regression and artificial neural network have been used. Decrease in radon concentration was recorded prior to some earthquakes that occurred during the observation period. Some false anomalies were also recorded which may be attributed to the ongoing crustal deformation which was not major enough to produce an earthquake.

  12. Performance analysis of two-way amplify and forward relaying with adaptive modulation over multiple relay network

    KAUST Repository

    Hwang, Kyusung; Ko, Youngchai; Alouini, Mohamed-Slim

    2011-01-01

    In this letter, we propose two-way amplify-and-forward relaying in conjunction with adaptive modulation in order to improve spectral efficiency of relayed communication systems while monitoring the required error performance. We also consider a multiple relay network where only the best relay node is utilized so that the diversity order increases while maintaining a low complexity of implementation as the number of relays increases. Based on the best relay selection criterion, we offer an upper bound on the signal-to-noise ratio to keep the performance analysis tractable. Our numerical examples show that the proposed system offers a considerable gain in spectral efficiency while satisfying the error rate requirements. © 2011 IEEE.

  13. Cooperative Transmission in Mobile Wireless Sensor Networks with Multiple Carrier Frequency Offsets: A Double-Differential Approach

    Directory of Open Access Journals (Sweden)

    Kun Zhao

    2014-01-01

    Full Text Available As a result of the rapidly increasing mobility of sensor nodes, mobile wireless sensor networks (MWSNs would be subject to multiple carrier frequency offsets (MCFOs, which result in time-varying channels and drastically degrade the network performance. To enhance the performance of such MWSNs, we propose a relay selection (RS based double-differential (DD cooperative transmission scheme, termed RSDDCT, in which the best relay sensor node is selected to forward the source sensor node’s signals to the destination sensor node with the detect-and-forward (DetF protocol. Assuming a Rayleigh fading environment, first, exact closed-form expressions for the outage probability and average bit error rate (BER of the RSDDCT scheme are derived. Then, simple and informative asymptotic outage probability and average BER expressions at the large signal-to-noise ratio (SNR regime are presented, which reveal that the RSDDCT scheme can achieve full diversity. Furthermore, the optimum power allocation strategy in terms of minimizing the average BER is investigated, and simple analytical solutions are obtained. Simulation results demonstrate that the proposed RSDDCT scheme can achieve excellent performance over fading channels in the presence of unknown random MCFOs. It is also shown that the proposed optimum power allocation strategy offers substantial average BER performance improvement over the equal power allocation strategy.

  14. Collective Influence of Multiple Spreaders Evaluated by Tracing Real Information Flow in Large-Scale Social Networks.

    Science.gov (United States)

    Teng, Xian; Pei, Sen; Morone, Flaviano; Makse, Hernán A

    2016-10-26

    Identifying the most influential spreaders that maximize information flow is a central question in network theory. Recently, a scalable method called "Collective Influence (CI)" has been put forward through collective influence maximization. In contrast to heuristic methods evaluating nodes' significance separately, CI method inspects the collective influence of multiple spreaders. Despite that CI applies to the influence maximization problem in percolation model, it is still important to examine its efficacy in realistic information spreading. Here, we examine real-world information flow in various social and scientific platforms including American Physical Society, Facebook, Twitter and LiveJournal. Since empirical data cannot be directly mapped to ideal multi-source spreading, we leverage the behavioral patterns of users extracted from data to construct "virtual" information spreading processes. Our results demonstrate that the set of spreaders selected by CI can induce larger scale of information propagation. Moreover, local measures as the number of connections or citations are not necessarily the deterministic factors of nodes' importance in realistic information spreading. This result has significance for rankings scientists in scientific networks like the APS, where the commonly used number of citations can be a poor indicator of the collective influence of authors in the community.

  15. Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation.

    Science.gov (United States)

    Brosch, Tom; Tang, Lisa Y W; Youngjin Yoo; Li, David K B; Traboulsee, Anthony; Tam, Roger

    2016-05-01

    We propose a novel segmentation approach based on deep 3D convolutional encoder networks with shortcut connections and apply it to the segmentation of multiple sclerosis (MS) lesions in magnetic resonance images. Our model is a neural network that consists of two interconnected pathways, a convolutional pathway, which learns increasingly more abstract and higher-level image features, and a deconvolutional pathway, which predicts the final segmentation at the voxel level. The joint training of the feature extraction and prediction pathways allows for the automatic learning of features at different scales that are optimized for accuracy for any given combination of image types and segmentation task. In addition, shortcut connections between the two pathways allow high- and low-level features to be integrated, which enables the segmentation of lesions across a wide range of sizes. We have evaluated our method on two publicly available data sets (MICCAI 2008 and ISBI 2015 challenges) with the results showing that our method performs comparably to the top-ranked state-of-the-art methods, even when only relatively small data sets are available for training. In addition, we have compared our method with five freely available and widely used MS lesion segmentation methods (EMS, LST-LPA, LST-LGA, Lesion-TOADS, and SLS) on a large data set from an MS clinical trial. The results show that our method consistently outperforms these other methods across a wide range of lesion sizes.

  16. Collective Influence of Multiple Spreaders Evaluated by Tracing Real Information Flow in Large-Scale Social Networks

    Science.gov (United States)

    Teng, Xian; Pei, Sen; Morone, Flaviano; Makse, Hernán A.

    2016-01-01

    Identifying the most influential spreaders that maximize information flow is a central question in network theory. Recently, a scalable method called “Collective Influence (CI)” has been put forward through collective influence maximization. In contrast to heuristic methods evaluating nodes’ significance separately, CI method inspects the collective influence of multiple spreaders. Despite that CI applies to the influence maximization problem in percolation model, it is still important to examine its efficacy in realistic information spreading. Here, we examine real-world information flow in various social and scientific platforms including American Physical Society, Facebook, Twitter and LiveJournal. Since empirical data cannot be directly mapped to ideal multi-source spreading, we leverage the behavioral patterns of users extracted from data to construct “virtual” information spreading processes. Our results demonstrate that the set of spreaders selected by CI can induce larger scale of information propagation. Moreover, local measures as the number of connections or citations are not necessarily the deterministic factors of nodes’ importance in realistic information spreading. This result has significance for rankings scientists in scientific networks like the APS, where the commonly used number of citations can be a poor indicator of the collective influence of authors in the community. PMID:27782207

  17. Investigating multiple dysregulated pathways in rheumatoid arthritis based on pathway interaction network.

    Science.gov (United States)

    Song, Xian-Dong; Song, Xian-Xu; Liu, Gui-Bo; Ren, Chun-Hui; Sun, Yuan-Bo; Liu, Ke-Xin; Liu, Bo; Liang, Shuang; Zhu, Zhu

    2018-03-01

    The traditional methods of identifying biomarkers in rheumatoid arthritis (RA) have focussed on the differentially expressed pathways or individual pathways, which however, neglect the interactions between pathways. To better understand the pathogenesis of RA, we aimed to identify dysregulated pathway sets using a pathway interaction network (PIN), which considered interactions among pathways. Firstly, RA-related gene expression profile data, protein-protein interactions (PPI) data and pathway data were taken up from the corresponding databases. Secondly, principal component analysis method was used to calculate the pathway activity of each of the pathway, and then a seed pathway was identified using data gleaned from the pathway activity. A PIN was then constructed based on the gene expression profile, pathway data, and PPI information. Finally, the dysregulated pathways were extracted from the PIN based on the seed pathway using the method of support vector machines and an area under the curve (AUC) index. The PIN comprised of a total of 854 pathways and 1064 pathway interactions. The greatest change in the activity score between RA and control samples was observed in the pathway of epigenetic regulation of gene expression, which was extracted and regarded as the seed pathway. Starting with this seed pathway, one maximum pathway set containing 10 dysregulated pathways was extracted from the PIN, having an AUC of 0.8249, and the result indicated that this pathway set could distinguish RA from the controls. These 10 dysregulated pathways might be potential biomarkers for RA diagnosis and treatment in the future.

  18. Computational Depth of Anesthesia via Multiple Vital Signs Based on Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Muammar Sadrawi

    2015-01-01

    Full Text Available This study evaluated the depth of anesthesia (DoA index using artificial neural networks (ANN which is performed as the modeling technique. Totally 63-patient data is addressed, for both modeling and testing of 17 and 46 patients, respectively. The empirical mode decomposition (EMD is utilized to purify between the electroencephalography (EEG signal and the noise. The filtered EEG signal is subsequently extracted to achieve a sample entropy index by every 5-second signal. Then, it is combined with other mean values of vital signs, that is, electromyography (EMG, heart rate (HR, pulse, systolic blood pressure (SBP, diastolic blood pressure (DBP, and signal quality index (SQI to evaluate the DoA index as the input. The 5 doctor scores are averaged to obtain an output index. The mean absolute error (MAE is utilized as the performance evaluation. 10-fold cross-validation is performed in order to generalize the model. The ANN model is compared with the bispectral index (BIS. The results show that the ANN is able to produce lower MAE than BIS. For the correlation coefficient, ANN also has higher value than BIS tested on the 46-patient testing data. Sensitivity analysis and cross-validation method are applied in advance. The results state that EMG has the most effecting parameter, significantly.

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

    Science.gov (United States)

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

    2017-01-01

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

  20. A social and ecological assessment of tropical land uses at multiple scales: the Sustainable Amazon Network

    Science.gov (United States)

    Gardner, Toby A.; Ferreira, Joice; Barlow, Jos; Lees, Alexander C.; Parry, Luke; Vieira, Ima Célia Guimarães; Berenguer, Erika; Abramovay, Ricardo; Aleixo, Alexandre; Andretti, Christian; Aragão, Luiz E. O. C.; Araújo, Ivanei; de Ávila, Williams Souza; Bardgett, Richard D.; Batistella, Mateus; Begotti, Rodrigo Anzolin; Beldini, Troy; de Blas, Driss Ezzine; Braga, Rodrigo Fagundes; Braga, Danielle de Lima; de Brito, Janaína Gomes; de Camargo, Plínio Barbosa; Campos dos Santos, Fabiane; de Oliveira, Vívian Campos; Cordeiro, Amanda Cardoso Nunes; Cardoso, Thiago Moreira; de Carvalho, Déborah Reis; Castelani, Sergio André; Chaul, Júlio Cézar Mário; Cerri, Carlos Eduardo; Costa, Francisco de Assis; da Costa, Carla Daniele Furtado; Coudel, Emilie; Coutinho, Alexandre Camargo; Cunha, Dênis; D'Antona, Álvaro; Dezincourt, Joelma; Dias-Silva, Karina; Durigan, Mariana; Esquerdo, Júlio César Dalla Mora; Feres, José; Ferraz, Silvio Frosini de Barros; Ferreira, Amanda Estefânia de Melo; Fiorini, Ana Carolina; da Silva, Lenise Vargas Flores; Frazão, Fábio Soares; Garrett, Rachel; Gomes, Alessandra dos Santos; Gonçalves, Karoline da Silva; Guerrero, José Benito; Hamada, Neusa; Hughes, Robert M.; Igliori, Danilo Carmago; Jesus, Ederson da Conceição; Juen, Leandro; Junior, Miércio; Junior, José Max Barbosa de Oliveira; Junior, Raimundo Cosme de Oliveira; Junior, Carlos Souza; Kaufmann, Phil; Korasaki, Vanesca; Leal, Cecília Gontijo; Leitão, Rafael; Lima, Natália; Almeida, Maria de Fátima Lopes; Lourival, Reinaldo; Louzada, Júlio; Nally, Ralph Mac; Marchand, Sébastien; Maués, Márcia Motta; Moreira, Fátima M. S.; Morsello, Carla; Moura, Nárgila; Nessimian, Jorge; Nunes, Sâmia; Oliveira, Victor Hugo Fonseca; Pardini, Renata; Pereira, Heloisa Correia; Pompeu, Paulo Santos; Ribas, Carla Rodrigues; Rossetti, Felipe; Schmidt, Fernando Augusto; da Silva, Rodrigo; da Silva, Regina Célia Viana Martins; da Silva, Thiago Fonseca Morello Ramalho; Silveira, Juliana; Siqueira, João Victor; de Carvalho, Teotônio Soares; Solar, Ricardo R. C.; Tancredi, Nicola Savério Holanda; Thomson, James R.; Torres, Patrícia Carignano; Vaz-de-Mello, Fernando Zagury; Veiga, Ruan Carlo Stulpen; Venturieri, Adriano; Viana, Cecília; Weinhold, Diana; Zanetti, Ronald; Zuanon, Jansen

    2013-01-01

    Science has a critical role to play in guiding more sustainable development trajectories. Here, we present the Sustainable Amazon Network (Rede Amazônia Sustentável, RAS): a multidisciplinary research initiative involving more than 30 partner organizations working to assess both social and ecological dimensions of land-use sustainability in eastern Brazilian Amazonia. The research approach adopted by RAS offers three advantages for addressing land-use sustainability problems: (i) the collection of synchronized and co-located ecological and socioeconomic data across broad gradients of past and present human use; (ii) a nested sampling design to aid comparison of ecological and socioeconomic conditions associated with different land uses across local, landscape and regional scales; and (iii) a strong engagement with a wide variety of actors and non-research institutions. Here, we elaborate on these key features, and identify the ways in which RAS can help in highlighting those problems in most urgent need of attention, and in guiding improvements in land-use sustainability in Amazonia and elsewhere in the tropics. We also discuss some of the practical lessons, limitations and realities faced during the development of the RAS initiative so far. PMID:23610172

  1. Traffic Regulation on Wireless 802.11 Networks Using Multiple Queue Technique

    Science.gov (United States)

    Dhanal, Radhika J.; Patil, G. A.

    2010-11-01

    WLAN technologies are becoming increasingly popular and are platform for many future applications. IEEE 802.11 Wireless LAN (WLAN) is an excellent solution for the broadband wireless networking. This paper presents a simple approach to enhance the performance of real time (RT) and non-real time (NRT) services over the 802.11 WLAN by using some special queues. This requires the system to first identify the type of service and then use the appropriate scheduling algorithm. The admission control algorithm is used first to determine the admission of particular station. Deficit round robin algorithm is used to set the priorities to RT and NRT packets in order to increase the QoS of WLAN. So we can combine both these algorithms by implementing them one after another. The proposed scheme can improve Voice/Data/Video services through simple software upgrades by reducing the delay, jitter and increasing the throughput. Through simulation, we show that the proposed scheme can give better QoS than existing schemes.

  2. ASIC-dependent LTP at multiple glutamatergic synapses in amygdala network is required for fear memory.

    Science.gov (United States)

    Chiang, Po-Han; Chien, Ta-Chun; Chen, Chih-Cheng; Yanagawa, Yuchio; Lien, Cheng-Chang

    2015-05-19

    Genetic variants in the human ortholog of acid-sensing ion channel-1a subunit (ASIC1a) gene are associated with panic disorder and amygdala dysfunction. Both fear learning and activity-induced long-term potentiation (LTP) of cortico-basolateral amygdala (BLA) synapses are impaired in ASIC1a-null mice, suggesting a critical role of ASICs in fear memory formation. In this study, we found that ASICs were differentially expressed within the amygdala neuronal population, and the extent of LTP at various glutamatergic synapses correlated with the level of ASIC expression in postsynaptic neurons. Importantly, selective deletion of ASIC1a in GABAergic cells, including amygdala output neurons, eliminated LTP in these cells and reduced fear learning to the same extent as that found when ASIC1a was selectively abolished in BLA glutamatergic neurons. Thus, fear learning requires ASIC-dependent LTP at multiple amygdala synapses, including both cortico-BLA input synapses and intra-amygdala synapses on output neurons.

  3. Local Flexibility Market Design for Aggregators Providing Multiple Flexibility Services at Distribution Network Level

    Directory of Open Access Journals (Sweden)

    Pol Olivella-Rosell

    2018-04-01

    Full Text Available This paper presents a general description of local flexibility markets as a market-based management mechanism for aggregators. The high penetration of distributed energy resources introduces new flexibility services like prosumer or community self-balancing, congestion management and time-of-use optimization. This work is focused on the flexibility framework to enable multiple participants to compete for selling or buying flexibility. In this framework, the aggregator acts as a local market operator and supervises flexibility transactions of the local energy community. Local market participation is voluntary. Potential flexibility stakeholders are the distribution system operator, the balance responsible party and end-users themselves. Flexibility is sold by means of loads, generators, storage units and electric vehicles. Finally, this paper presents needed interactions between all local market stakeholders, the corresponding inputs and outputs of local market operation algorithms from participants and a case study to highlight the application of the local flexibility market in three scenarios. The local market framework could postpone grid upgrades, reduce energy costs and increase distribution grids’ hosting capacity.

  4. Computer Programming and Biomolecular Structure Studies: A Step beyond Internet Bioinformatics

    Science.gov (United States)

    Likic, Vladimir A.

    2006-01-01

    This article describes the experience of teaching structural bioinformatics to third year undergraduate students in a subject titled "Biomolecular Structure and Bioinformatics." Students were introduced to computer programming and used this knowledge in a practical application as an alternative to the well established Internet bioinformatics…

  5. Electrostatics in biomolecular simulations : where are we now and where are we heading?

    NARCIS (Netherlands)

    Karttunen, M.E.J.; Rottler, J.; Vattulainen, I.; Sagui, C.

    2008-01-01

    Chapter 2. In this review, we discuss current methods and developments in the treatment of electrostatic interactions in biomolecular and soft matter simulations. We review the current ‘work horses’, namely, Ewald summation based methods such the Particle-Mesh Ewald, and others, and also newer

  6. Improvements to the APBS biomolecular solvation software suite: Improvements to the APBS Software Suite

    Energy Technology Data Exchange (ETDEWEB)

    Jurrus, Elizabeth [Pacific Northwest National Laboratory, Richland Washington; Engel, Dave [Pacific Northwest National Laboratory, Richland Washington; Star, Keith [Pacific Northwest National Laboratory, Richland Washington; Monson, Kyle [Pacific Northwest National Laboratory, Richland Washington; Brandi, Juan [Pacific Northwest National Laboratory, Richland Washington; Felberg, Lisa E. [University of California, Berkeley California; Brookes, David H. [University of California, Berkeley California; Wilson, Leighton [University of Michigan, Ann Arbor Michigan; Chen, Jiahui [Southern Methodist University, Dallas Texas; Liles, Karina [Pacific Northwest National Laboratory, Richland Washington; Chun, Minju [Pacific Northwest National Laboratory, Richland Washington; Li, Peter [Pacific Northwest National Laboratory, Richland Washington; Gohara, David W. [St. Louis University, St. Louis Missouri; Dolinsky, Todd [FoodLogiQ, Durham North Carolina; Konecny, Robert [University of California San Diego, San Diego California; Koes, David R. [University of Pittsburgh, Pittsburgh Pennsylvania; Nielsen, Jens Erik [Protein Engineering, Novozymes A/S, Copenhagen Denmark; Head-Gordon, Teresa [University of California, Berkeley California; Geng, Weihua [Southern Methodist University, Dallas Texas; Krasny, Robert [University of Michigan, Ann Arbor Michigan; Wei, Guo-Wei [Michigan State University, East Lansing Michigan; Holst, Michael J. [University of California San Diego, San Diego California; McCammon, J. Andrew [University of California San Diego, San Diego California; Baker, Nathan A. [Pacific Northwest National Laboratory, Richland Washington; Brown University, Providence Rhode Island

    2017-10-24

    The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that has provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this manuscript, we discuss the models and capabilities that have recently been implemented within the APBS software package including: a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory based algorithm for determining pKa values, and an improved web-based visualization tool for viewing electrostatics.

  7. Affinity Capillary Electrophoresis – A Powerful Tool to Investigate Biomolecular Interactions

    Czech Academy of Sciences Publication Activity Database

    Kašička, Václav

    2017-01-01

    Roč. 30, č. 5 (2017), s. 248 ISSN 1471-6577 Institutional support: RVO:61388963 Keywords : capillary affinity electrophoresis * biomolecular interactions * binding constants Subject RIV: CB - Analytical Chemistry, Separation OBOR OECD: Analytical chemistry Impact factor: 0.663, year: 2016

  8. Adaptation of AMO-FBMC-OQAM in optical access network for accommodating asynchronous multiple access in OFDM-based uplink transmission

    Science.gov (United States)

    Jung, Sun-Young; Jung, Sang-Min; Han, Sang-Kook

    2015-01-01

    Exponentially expanding various applications in company with proliferation of mobile devices make mobile traffic exploded annually. For future access network, bandwidth efficient and asynchronous signals converged transmission technique is required in optical network to meet a huge bandwidth demand, while integrating various services and satisfying multiple access in perceived network resource. Orthogonal frequency division multiplexing (OFDM) is highly bandwidth efficient parallel transmission technique based on orthogonal subcarriers. OFDM has been widely studied in wired-/wireless communication and became a Long term evolution (LTE) standard. Consequently, OFDM also has been actively researched in optical network. However, OFDM is vulnerable frequency and phase offset essentially because of its sinc-shaped side lobes, therefore tight synchronism is necessary to maintain orthogonality. Moreover, redundant cyclic prefix (CP) is required in dispersive channel. Additionally, side lobes act as interference among users in multiple access. Thus, it practically hinders from supporting integration of various services and multiple access based on OFDM optical transmission In this paper, adaptively modulated optical filter bank multicarrier system with offset QAM (AMO-FBMC-OQAM) is introduced and experimentally investigated in uplink optical transmission to relax multiple access interference (MAI), while improving bandwidth efficiency. Side lobes are effectively suppressed by using FBMC, therefore the system becomes robust to path difference and imbalance among optical network units (ONUs), which increase bandwidth efficiency by reducing redundancy. In comparison with OFDM, a signal performance and an efficiency of frequency utilization are improved in the same experimental condition. It enables optical network to effectively support heterogeneous services and multiple access.

  9. ALTERNATIVAS BIOMOLECULARES EN EL TRATAMIENTO DE LA OBESIDAD

    Directory of Open Access Journals (Sweden)

    Fernando Lizcano

    2010-09-01

    Full Text Available

    Resumen

    La obesidad se ha convertido en un problema de salud pública que cobija tanto a países desarrollados como a aquellos en vía de desarrollo. En la mayoría de los casos las políticas de salud no han tenido el efecto deseado para reducir la prevalencia de esta patología y muchos de los fármacos útiles para contrarrestar la obesidad no han podido continuar en el mercado debido a serios efectos secundarios. Algunas alternativas terapéuticas más agresivas como la cirugías reductivas han demostrado una utilidad restringida. Incluso, recientes observaciones han puesto de manifiesto las consecuencias a largo plazo de este tipo de intervenciones.

    En la búsqueda de nuevas estrategias para el tratamiento de la obesidad se ha investigado, tanto en la propia célula grasa como en los genes que podrían ser modificados y cuya función está enfocada en regular el gasto calórico y la termogénesis adaptativa. Algunos de estos genes son modificados por factores de transcripción que pueden determinar la característica fenotípica de la célula grasa. Recientemente se ha observado que en la persona adulta es posible evidenciar vestigios de célula grasa parda que puede gastar energía en forma de calor y esta modificación podría ser una alternativa terapéutica en la obesidad. Nuestro grupo de investigación ha observado que mediante la modificación de la función de la proteína del retinoblastoma (pRb se pueden aumentar los genes que estimulan la pérdida calórica en el adipocito.

    Palabras clave: Grasa Parda, Obesidad, transcripción, EID1, transdiferenciación

    BIOMOLECULAR OPTIONS IN TREATING OBESITY

    Abstract

    Obesity is a public health issue for both developed and third world countries. Although many efforts have been made to reverse the trend of this prevalent pathology, no results have been obtained with public health policies in most cases. Furthermore, many medicines approved for

  10. Alcohol use among adolescent youth: the role of friendship networks and family factors in multiple school studies.

    Directory of Open Access Journals (Sweden)

    Cheng Wang

    Full Text Available To explore the co-evolution of friendship tie choice and alcohol use behavior among 1,284 adolescents from 12 small schools and 976 adolescents from one big school sampled in the National Longitudinal Study of Adolescent to Adult Health (AddHealth, we apply a Stochastic Actor-Based (SAB approach implemented in the R-based Simulation Investigation for Empirical Network Analysis (RSiena package. Our results indicate the salience of both peer selection and peer influence effects for friendship tie choice and adolescent drinking behavior. Concurrently, the main effect models indicate that parental monitoring and the parental home drinking environment affected adolescent alcohol use in the small school sample, and that parental home drinking environment affected adolescent drinking in the large school sample. In the small school sample, we detect an interaction between the parental home drinking environment and choosing friends that drink as they multiplicatively affect friendship tie choice. Our findings suggest that future research should investigate the synergistic effects of both peer and parental influences for adolescent friendship tie choices and drinking behavior. And given the tendency of adolescents to form ties with their friends' friends, and the evidence of local hierarchy in these networks, popular youth who do not drink may be uniquely positioned and uniquely salient as the highest rank of the hierarchy to cause anti-drinking peer influences to diffuse down the social hierarchy to less popular youth. As such, future interventions should harness prosocial peer influences simultaneously with strategies to increase parental support and monitoring among parents to promote affiliation with prosocial peers.

  11. Quantifying the topography of the intrinsic energy landscape of flexible biomolecular recognition

    Science.gov (United States)

    Chu, Xiakun; Gan, Linfeng; Wang, Erkang; Wang, Jin

    2013-01-01

    Biomolecular functions are determined by their interactions with other molecules. Biomolecular recognition is often flexible and associated with large conformational changes involving both binding and folding. However, the global and physical understanding for the process is still challenging. Here, we quantified the intrinsic energy landscapes of flexible biomolecular recognition in terms of binding–folding dynamics for 15 homodimers by exploring the underlying density of states, using a structure-based model both with and without considering energetic roughness. By quantifying three individual effective intrinsic energy landscapes (one for interfacial binding, two for monomeric folding), the association mechanisms for flexible recognition of 15 homodimers can be classified into two-state cooperative “coupled binding–folding” and three-state noncooperative “folding prior to binding” scenarios. We found that the association mechanism of flexible biomolecular recognition relies on the interplay between the underlying effective intrinsic binding and folding energy landscapes. By quantifying the whole global intrinsic binding–folding energy landscapes, we found strong correlations between the landscape topography measure Λ (dimensionless ratio of energy gap versus roughness modulated by the configurational entropy) and the ratio of the thermodynamic stable temperature versus trapping temperature, as well as between Λ and binding kinetics. Therefore, the global energy landscape topography determines the binding–folding thermodynamics and kinetics, crucial for the feasibility and efficiency of realizing biomolecular function. We also found “U-shape” temperature-dependent kinetic behavior and a dynamical cross-over temperature for dividing exponential and nonexponential kinetics for two-state homodimers. Our study provides a unique way to bridge the gap between theory and experiments. PMID:23754431

  12. A Multiple Case Study Discovering Part-Time Faculties' Perceptions of Their Professional Needs, Working Conditions, Social Network, and Job Satisfaction at Three Community Colleges

    Science.gov (United States)

    Millner-Harlee, Tanya

    2010-01-01

    This study employed a multiple case study design to evaluate the perspectives of part-time faculties at three community colleges in the Northeast. The purpose of this study was to discover how needs, working conditions, and social networks influence the part-time faculties' job satisfaction. Maslow (1954), Bourdieu (1986), and Herzberg, Mausner,…

  13. Network meta-analysis of randomized trials in multiple myeloma: efficacy and safety in relapsed/refractory patients.

    Science.gov (United States)

    Botta, Cirino; Ciliberto, Domenico; Rossi, Marco; Staropoli, Nicoletta; Cucè, Maria; Galeano, Teresa; Tagliaferri, Pierosandro; Tassone, Pierfrancesco

    2017-02-28

    Despite major therapeutic advancements, multiple myeloma (MM) is still incurable and relapsed/refractory multiple myeloma (RRMM) remains a challenge; the rational choice of the most appropriate regimen in this setting is currently undefined. We performed a systematic review and 2 standard pairwise meta-analyses to evaluate the efficacy of regimens that have been directly compared with bortezomib or immunomodulatory imide drugs (IMiDs) in head-to-head clinical trials and a network meta-analysis (NMA) to determine the relevance of each regimen on the basis of all the available direct and indirect evidence. Sixteen trials were included in the pairwise meta-analyses, and 18 trials were included in the NMA. Pairwise meta-analyses showed that a 3-drug regimen (bortezomib- or IMiD-based) was superior to a 2-drug regimen in progression-free-survival (PFS) and overall response rate (ORR). NMA showed that an IMiD backbone associated with anti-MM monoclonal antibodies (mAbs) (preferably) or proteasome inhibitors had the highest probability of being the most effective regimen with the lowest toxicity. The combination of daratumumab, lenalidomide, and dexamethasone ranked as the first regimen in terms of activity, efficacy, and tolerability according to the average value between surface under the cumulative ranking curve of PFS, overall survival, ORR, complete response rate, and safety. This is the first NMA comparing all currently available regimens evaluated in published randomized trials for the treatment of RRMM, but our results need to be interpreted taking into account differences in their patient populations. Our analysis suggests that IMiDs plus new anti-MM mAb-containing regimens are the most active therapeutic option in RRMM.

  14. Carotenoid Biosynthetic Pathways Are Regulated by a Network of Multiple Cascades of Alternative Sigma Factors in Azospirillum brasilense Sp7.

    Science.gov (United States)

    Rai, Ashutosh Kumar; Dubey, Ashutosh Prakash; Kumar, Santosh; Dutta, Debashis; Mishra, Mukti Nath; Singh, Bhupendra Narain; Tripathi, Anil Kumar

    2016-11-01

    Carotenoids constitute an important component of the defense system against photooxidative stress in bacteria. In Azospirillum brasilense Sp7, a nonphotosynthetic rhizobacterium, carotenoid synthesis is controlled by a pair of extracytoplasmic function sigma factors (RpoEs) and their cognate zinc-binding anti-sigma factors (ChrRs). Its genome harbors two copies of the gene encoding geranylgeranyl pyrophosphate synthase (CrtE), the first critical step in the carotenoid biosynthetic pathway in bacteria. Inactivation of each of two crtE paralogs found in A. brasilense caused reduction in carotenoid content, suggesting their involvement in carotenoid synthesis. However, the effect of crtE1 deletion was more pronounced than that of crtE2 deletion. Out of the five paralogs of rpoH in A. brasilense, overexpression of rpoH1 and rpoH2 enhanced carotenoid synthesis. Promoters of crtE2 and rpoH2 were found to be dependent on RpoH2 and RpoE1, respectively. Using a two-plasmid system in Escherichia coli, we have shown that the crtE2 gene of A. brasilense Sp7 is regulated by two cascades of sigma factors: one consisting of RpoE1and RpoH2 and the other consisting of RpoE2 and RpoH1. In addition, expression of crtE1 was upregulated indirectly by RpoE1 and RpoE2. This study shows, for the first time in any carotenoid-producing bacterium, that the regulation of carotenoid biosynthetic pathway involves a network of multiple cascades of alternative sigma factors. Carotenoids play a very important role in coping with photooxidative stress in prokaryotes and eukaryotes. Although extracytoplasmic function (ECF) sigma factors are known to directly regulate the expression of carotenoid biosynthetic genes in bacteria, regulation of carotenoid biosynthesis by one or multiple cascades of sigma factors had not been reported. This study provides the first evidence of the involvement of multiple cascades of sigma factors in the regulation of carotenoid synthesis in any bacterium by showing the

  15. The use of artificial neural networks and multiple linear regression to predict rate of medical waste generation

    International Nuclear Information System (INIS)

    Jahandideh, Sepideh; Jahandideh, Samad; Asadabadi, Ebrahim Barzegari; Askarian, Mehrdad; Movahedi, Mohammad Mehdi; Hosseini, Somayyeh; Jahandideh, Mina

    2009-01-01

    Prediction of the amount of hospital waste production will be helpful in the storage, transportation and disposal of hospital waste management. Based on this fact, two predictor models including artificial neural networks (ANNs) and multiple linear regression (MLR) were applied to predict the rate of medical waste generation totally and in different types of sharp, infectious and general. In this study, a 5-fold cross-validation procedure on a database containing total of 50 hospitals of Fars province (Iran) were used to verify the performance of the models. Three performance measures including MAR, RMSE and R 2 were used to evaluate performance of models. The MLR as a conventional model obtained poor prediction performance measure values. However, MLR distinguished hospital capacity and bed occupancy as more significant parameters. On the other hand, ANNs as a more powerful model, which has not been introduced in predicting rate of medical waste generation, showed high performance measure values, especially 0.99 value of R 2 confirming the good fit of the data. Such satisfactory results could be attributed to the non-linear nature of ANNs in problem solving which provides the opportunity for relating independent variables to dependent ones non-linearly. In conclusion, the obtained results showed that our ANN-based model approach is very promising and may play a useful role in developing a better cost-effective strategy for waste management in future.

  16. Multiple linear regression and artificial neural networks for delta-endotoxin and protease yields modelling of Bacillus thuringiensis.

    Science.gov (United States)

    Ennouri, Karim; Ben Ayed, Rayda; Triki, Mohamed Ali; Ottaviani, Ennio; Mazzarello, Maura; Hertelli, Fathi; Zouari, Nabil

    2017-07-01

    The aim of the present work was to develop a model that supplies accurate predictions of the yields of delta-endotoxins and proteases produced by B. thuringiensis var. kurstaki HD-1. Using available medium ingredients as variables, a mathematical method, based on Plackett-Burman design (PB), was employed to analyze and compare data generated by the Bootstrap method and processed by multiple linear regressions (MLR) and artificial neural networks (ANN) including multilayer perceptron (MLP) and radial basis function (RBF) models. The predictive ability of these models was evaluated by comparison of output data through the determination of coefficient (R 2 ) and mean square error (MSE) values. The results demonstrate that the prediction of the yields of delta-endotoxin and protease was more accurate by ANN technique (87 and 89% for delta-endotoxin and protease determination coefficients, respectively) when compared with MLR method (73.1 and 77.2% for delta-endotoxin and protease determination coefficients, respectively), suggesting that the proposed ANNs, especially MLP, is a suitable new approach for determining yields of bacterial products that allow us to make more appropriate predictions in a shorter time and with less engineering effort.

  17. Computerized detection of multiple sclerosis candidate regions based on a level set method using an artificial neural network

    International Nuclear Information System (INIS)

    Kuwazuru, Junpei; Magome, Taiki; Arimura, Hidetaka; Yamashita, Yasuo; Oki, Masafumi; Toyofuku, Fukai; Kakeda, Shingo; Yamamoto, Daisuke

    2010-01-01

    Yamamoto et al. developed the system for computer-aided detection of multiple sclerosis (MS) candidate regions. In a level set method in their proposed method, they employed the constant threshold value for the edge indicator function related to a speed function of the level set method. However, it would be appropriate to adjust the threshold value to each MS candidate region, because the edge magnitudes in MS candidates differ from each other. Our purpose of this study was to develop a computerized detection of MS candidate regions in MR images based on a level set method using an artificial neural network (ANN). To adjust the threshold value for the edge indicator function in the level set method to each true positive (TP) and false positive (FP) region, we constructed the ANN. The ANN could provide the suitable threshold value for each candidate region in the proposed level set method so that TP regions can be segmented and FP regions can be removed. Our proposed method detected MS regions at a sensitivity of 82.1% with 0.204 FPs per slice and similarity index of MS candidate regions was 0.717 on average. (author)

  18. A Collaborative Approach for Monitoring Nodes Behavior during Spectrum Sensing to Mitigate Multiple Attacks in Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Mahmoud Khasawneh

    2017-01-01

    Full Text Available Spectrum sensing is the first step to overcome the spectrum scarcity problem in Cognitive Radio Networks (CRNs wherein all unutilized subbands in the radio environment are explored for better spectrum utilization. Adversary nodes can threaten these spectrum sensing results by launching passive and active attacks that prevent legitimate nodes from using the spectrum efficiently. Securing the spectrum sensing process has become an important issue in CRNs in order to ensure reliable and secure spectrum sensing and fair management of resources. In this paper, a novel collaborative approach during spectrum sensing process is proposed. It monitors the behavior of sensing nodes and identifies the malicious and misbehaving sensing nodes. The proposed approach measures the node’s sensing reliability using a value called belief level. All the sensing nodes are grouped into a specific number of clusters. In each cluster, a sensing node is selected as a cluster head that is responsible for collecting sensing-reputation reports from different cognitive nodes about each node in the same cluster. The cluster head analyzes information to monitor and judge the nodes’ behavior. By simulating the proposed approach, we showed its importance and its efficiency for achieving better spectrum security by mitigating multiple passive and active attacks.

  19. Optical coherence tomography angiography indicates associations of the retinal vascular network and disease activity in multiple sclerosis.

    Science.gov (United States)

    Feucht, Nikolaus; Maier, Mathias; Lepennetier, Gildas; Pettenkofer, Moritz; Wetzlmair, Carmen; Daltrozzo, Tanja; Scherm, Pauline; Zimmer, Claus; Hoshi, Muna-Miriam; Hemmer, Bernhard; Korn, Thomas; Knier, Benjamin

    2018-01-01

    Patients with multiple sclerosis (MS) and clinically isolated syndrome (CIS) may show alterations of retinal layer architecture as measured by optical coherence tomography. Little is known about changes in the retinal vascular network during MS. To characterize retinal vessel structures in patients with MS and CIS and to test for associations with MS disease activity. In all, 42 patients with MS or CIS and 50 healthy controls underwent retinal optical coherence tomography angiography (OCT-A) with analysis of the superficial and deep vascular plexuses and the choriocapillaries. We tested OCT-A parameters for associations with retinal layer volumes, history of optic neuritis (ON), and the retrospective disease activity. Inner retinal layer volumes correlated positively with the density of both the superficial and deep vascular plexuses. Eyes of MS/CIS patients with a history of ON revealed reduced vessel densities of the superficial and deep vascular plexuses as compared to healthy controls. Higher choriocapillary vessel densities were associated with ongoing inflammatory disease activity during 24 months prior to OCT-A examination in MS and CIS patients. Optic neuritis is associated with rarefaction of the superficial and deep retinal vessels. Alterations of the choriocapillaries might be linked to disease activity in MS.

  20. Prediction of Currency Volume Issued in Taiwan Using a Hybrid Artificial Neural Network and Multiple Regression Approach

    Directory of Open Access Journals (Sweden)

    Yuehjen E. Shao

    2013-01-01

    Full Text Available Because the volume of currency issued by a country always affects its interest rate, price index, income levels, and many other important macroeconomic variables, the prediction of currency volume issued has attracted considerable attention in recent years. In contrast to the typical single-stage forecast model, this study proposes a hybrid forecasting approach to predict the volume of currency issued in Taiwan. The proposed hybrid models consist of artificial neural network (ANN and multiple regression (MR components. The MR component of the hybrid models is established for a selection of fewer explanatory variables, wherein the selected variables are of higher importance. The ANN component is then designed to generate forecasts based on those important explanatory variables. Subsequently, the model is used to analyze a real dataset of Taiwan's currency from 1996 to 2011 and twenty associated explanatory variables. The prediction results reveal that the proposed hybrid scheme exhibits superior forecasting performance for predicting the volume of currency issued in Taiwan.